From THE DIVISION OF INFECTIOUS DISEASES ...

From THE DIVISION OF INFECTIOUS DISEASES, DEPARTMENT OF MEDICINE HUDDINGE, Karolinska Institutet, Stockholm, Sweden

THE ROLE OF MICROBIAL TRANSLOCATION AND GUT MICROBIOTA IN HIV-1 INFECTION Jan Vesterbacka

Stockholm 2017

All previously published papers were reproduced with permission from the publisher. Published by Karolinska Institutet. © Jan Vesterbacka, 2017 ISBN 978-91-7676-671-2 Printed by E-print AB 2017

The role of microbial translocation and gut microbiota in HIV-1 infection

THESIS FOR DOCTORAL DEGREE (Ph.D.) AKADEMISK AVHANDLING som för avläggande av medicine doktorsexamen vid Karolinska Institutet offentligen försvaras i föreläsningssal M41, Karolinska Universitetssjukhuset, Huddinge Fredagen den 29 september 2017, kl 09.00

By

Jan Vesterbacka

Principal Supervisor: Piotr Nowak Karolinska Institutet Department of Medicine Huddinge, Unit of Infection and Dermatology Co-supervisor: Anders Sönnerborg Karolinska Institutet Department of Medicine Huddinge, Unit of Infection and Dermatology

Opponent: Irini Sereti, MD, Chief, HIV Pathogenesis Section National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, USA Examination Board: Associate Professor Volkan Özenci Karolinska Institutet Department of Laboratory Medicine Division of Clinical Microbiology Associate Professor Christer Lidman Karolinska Institutet Department of Medicine, Huddinge Unit of Infection and Dermatology Professor Eva Sverremark-Ekström Stockholm University Department of Molecular Biosciences The Wenner-Gren Institute

ABSTRACT HIV-1 infection is characterized by persistent systemic inflammation and immune activation, even in patients receiving effective antiretroviral therapy (ART). Translocation of microbial compounds from a leaky gut to systemic circulation, so called microbial translocation (MT), is a major driver of the immune activation. Additionally, gut microbiota dysbiosis in HIV-1 infected patients further facilitate and fuel MT. The objectives of this thesis were to study: 

how different ART regimens and usage of antibiotics affect markers of MT (I, II)



the alternations of gut microbiota during HIV-1 infection and the effect of ART (III,IV)

In a clinical randomized trial, HIV-1 infected subjects started ART based on efavirenz (n=37) or ritonavir-boosted lopinavir (n=34). Levels of MT markers and of enterocyte death were elevated at baseline (BL), and MT markers declined until follow up after 72 weeks, but the reduction of anti-flagellin IgG antibodies was significant only in lopinavir treated patients. Levels of Intestinal Fatty Acid Binding Protein (I-FABP) remained unchanged at 72 weeks, but were temporarily increased after one month in efavirenz treated patients. 29 subjects with concomitant use of antibiotics had superior reduction of soluble CD14 (sCD14) levels. These data show that choice of ART and antibiotics usage could affect the kinetics of some MT markers. To further explore the impact of antibiotics usage on MT, we performed a longitudinal study on HIV-1 patients initiating ART without (n=13) or with (n=13) co-trimoxazole (TMP-SMX) as prophylaxis against Pneumocystis jirovecii. Following ART, levels of LPS-binding protein (LBP) were reduced only in the TMP-SMX group, whilst levels of sCD14 declined in both groups after one year. The LBP decrease remained significant in a multivariate analysis model adjusting for co-variates including BL CD4+ T-cell count. This study confirmed that concomitant use of antibiotics and ART in severely immune deteriorated individuals may beneficially influence the kinetics of MT markers. In the third study, the composition of gut microbiota was determined by 16S rRNA sequencing in 28 HIV-1 progressors, 3 EC and 9 uninfected controls at BL, and additionally after ten months of ART in 16 subjects. Gut microbiome α-diversity was reduced in HIV-1 infected individuals as compared to controls, and further declined after introduction of ART. At BL, α-diversity was positively correlated with CD4+ T-cell counts, but in contrary several markers of MT/immune activation were inversely correlated. Microbiome of EC had the lowest interindividual variation (ß-diversity), clustering together in PCoA analysis. The bacterial composition at genus level was altered in HIV-1 progressors with higher abundance of Lactobacillus, and depletion of Lachnobacterium, Faecalibacterium and Hemophilus. Thus, this study showed that the alternations of gut microbiota during HIV-1 infection are

associated with the level of immune dysfunction, and that almost one year of ART does not restore the shifts in the gut microbiome. In the last work, we studied the gut microbiome of 16 EC in relation to 32 matched ART naive HIV-1 positive individuals and 16 uninfected controls. The number of observed genera and richness indices Chao-1 and ACE were significantly higher in EC as compared to naive patients. The gut microbiota in EC was enriched in genera Succinivibrio, Sutterella, Rhizobium, Delftia, Anaerofilum and Oscillospira, whilst Blautia and Anaerostipes were reduced. Determination of inferred bacterial functionality by PICRUSt analysis revealed that carbohydrate metabolism related genes were depleted in EC. In contrary, pathways related to fatty acid metabolism, PPAR-signaling and lipid biosynthesis proteins were more abundant in EC vs naive. The kynurenine pathway of tryptophan metabolism was altered only during progressive HIV-1 infection, and kynurenine tryptophan (K/T) ratio was inversely associated with gut microbiota richness. This study shows that EC have richer gut microbiota than untreated HIV-1 patients with progressive infection, with a unique bacterial composition and a distinct metabolic profile which may be involved in the control of HIV-1. In summary, data from the studies in my thesis reveal that MT in HIV-1 infection is reduced by ART but also that the choice of ART influences this decline. Additionally, the antibiotics usage may affect the levels of MT. The complexity, composition and functionality of gut microbiota are disturbed in HIV-1 infected individuals with progressive disease, whilst EC have a unique gut microbiota profile that eventually contributes to their control of HIV-1.

LIST OF SCIENTIFIC PAPERS

I. Vesterbacka Jan, Nowak Piotr, Barqasho Babilonia, Abdurahman Samir, Nyström Jessica, Nilsson Staffan, Funaoka Hiroyuki, Kanda Tatsuo, Andersson Lars-Magnus, Gisslèn Magnus, Sönnerborg Anders. Kinetics of microbial translocation markers in patients on efavirenz or lopinavir/r based antiretroviral therapy. PLoS One. 2013;8(1):e55038. doi: 10.1371/journal.pone.0055038. Epub 2013 Jan 28. II. Vesterbacka Jan, Barqasho Babilonia, Häggblom Amanda, Nowak Piotr. Effects of Co-Trimoxazole on Microbial Translocation in HIV-1-Infected Patients Initiating Antiretroviral Therapy. AIDS Res Hum Retroviruses. 2015 Aug;31(8):830-6. doi: 10.1089/AID.2014.0366. Epub 2015 Jun 15. III. Nowak Piotr, Troseid Marius, Avershina Ekatarina, Barqasho Babilonia, Neogi Ujjwal, Holm Kristian, Hov Johannes R, Noyan Kajsa, Vesterbacka Jan, Svärd Jenny, Rudi Knut, Sönnerborg Anders. Gut microbiota diversity predicts immune status in HIV-1 infection. AIDS. 2015 Nov 28;29(18):240918. doi: 10.1097/QAD.0000000000000869. IV. Vesterbacka Jan, Rivera Javier, Noyan Kajsa, Parera Mariona, Neogi Ujjwal, Calle Malu, Paredes Roger, Sönnerborg Anders, Noguera-Julian Marc, Nowak Piotr. Richer gut microbiota with distinct metabolic profile in HIV infected Elite Controllers. Sci Rep. 2017 Jul 24;7(1):6269. doi: 10.1038/s41598-017-06675-1.

CONTENTS 1 2

3 4

5

Introduction ..................................................................................................................... 1 Background...................................................................................................................... 2 2.1 HIV characteristics ................................................................................................ 2 2.2 Epidemiology ........................................................................................................ 2 2.3 HIV-1, immune activation and inflammation ...................................................... 3 2.4 Microbial translocation ......................................................................................... 5 2.5 Markers of microbial translocation ....................................................................... 5 2.6 Microbial translocation in HIV-1 infection .......................................................... 7 2.7 Microbial translocation and antiretroviral therapy ............................................... 9 2.8 The human gut microbiota .................................................................................. 10 2.9 Gut microbiota in HIV-1 infection ..................................................................... 10 2.10 Elite Controllers................................................................................................... 11 Aims............................................................................................................................... 13 Methods ......................................................................................................................... 14 4.1 Subjects ................................................................................................................ 14 4.2 Flow cytometry and viral load ............................................................................ 15 4.3 Isolation of Peripheral Blood Mononuclear Cells and Immunophenotyping ........................................................................................... 15 4.4 Markers of microbial translocation ..................................................................... 15 4.5 Soluble markers of inflammation and tryptophan catabolism ........................... 16 4.6 Fecal sample collection ....................................................................................... 16 4.7 Extraction of DNA from stool samples .............................................................. 16 4.8 Sequencing of gut microbiota ............................................................................. 17 4.9 Sequence analysis ................................................................................................ 17 4.10 Statistical analyses ............................................................................................... 18 4.10.1 Paper I + II............................................................................................... 18 4.10.2 Paper III ................................................................................................... 18 4.10.3 Paper IV ................................................................................................... 18 4.11 Ethical permits ..................................................................................................... 19 Results ........................................................................................................................... 20 5.1 Paper I+II ............................................................................................................. 20 5.1.1 Levels of LPS .......................................................................................... 20 5.1.2 Levels of sCD14 ...................................................................................... 21 5.1.3 Levels of LBP.......................................................................................... 21 5.1.4 Levels of anti-flagellin antibodies .......................................................... 21 5.1.5 Levels of I-FABP .................................................................................... 21 5.1.6 Antibiotics and microbial translocation markers ................................... 22 5.2 Paper III+IV......................................................................................................... 22 5.2.1 Gut microbiota diversity in treatment naive patients ............................. 22 5.2.1.1

α-diversity................................................................................................ 22

5.2.1.2 5.2.2 5.2.3 5.2.4 5.2.5 5.2.6

6 7 8 9 10 11

ß-diversity ................................................................................................24 Composition of gut microbiota in treatment naive patients ...................25 α-diversity, immune status and inflammation ........................................26 Tryptophan catabolism and gut microbiota ............................................27 Effects of ART on gut microbiota ..........................................................27 Elite controllers .......................................................................................27

5.2.6.1

Microbial translocation, inflammation and tryptophan catabolism .......27

5.2.6.2

Gut microbiota.........................................................................................28

5.2.6.3

Inferred functionality of gut microbiota .................................................29

Discussion ......................................................................................................................31 Conclusions ...................................................................................................................36 Future plans and perspectives .......................................................................................37 Sammanfattning på svenska ..........................................................................................38 Acknowledgements .......................................................................................................40 References .....................................................................................................................42

LIST OF ABBREVIATIONS AIDS

Acquired Immune Deficiency Syndrome

ART

Antiretroviral therapy

EC

Elite Controllers

EFV

Efavirenz

ELISA

Enzyme-linked immunosorbent assay

GALT

Gut Associated Lymphoid Tissue

GI

Gastrointestinal

HIV-1

Human immunodeficiency virus type 1

hS-CRP

High sensitive C-reactive protein

I-FABP

Intestinal Fatty Acid Binding Protein

Ig

Immunoglobulin

IL

Interleukin

LPS

Lipopolysaccharide

LBP

Lipopolysaccharide Binding Protein

LPV

Boosted lopinavir

MD-2

Lymphocyte antigen 96

MT

Microbial translocation

NGS

Next generation sequencing

PBMC

Peripheral blood mononuclear cell

PCR

Polymerase chain reaction

sCD14

Soluble Cluster of Differentiation 14

sCD163

Soluble Cluster of Differentiation 163

TLR

Toll-like receptor

TMP-SMX

Co-trimoxazole

TNF

Tumor necrosis factor

UNAIDS

Joint United Nations Program on HIV/AIDS

1

INTRODUCTION

Since the appearance of the human immunodeficiency virus (HIV) epidemic, tremendous progress has been achieved in the treatment and care of HIV infected patients. The breakthrough with highly active antiretroviral therapy (HAART) at 1995-96 dramatically decreased AIDS related mortality and reduced prevalence of HIV related conditions. A systemic immune activation was early identified as a hallmark of HIV-1 infection in untreated patients and this feature persists even in patients treated with combined antiretroviral treatment (ART), regardless of undetectable plasma viral load. The chronic immune activation and inflammation contribute to a higher risk of both AIDS related clinical events and to non-AIDS related conditions1,2. Following initiation of ART, the levels of both cellular and serum biomarkers of immune activation are thus reduced, but not to the levels present in healthy controls3,4. There are several potential contributors fueling the low-grade inflammation, in addition to HIV itself. Co-infections with other viruses inducing an inflammatory response like cytomegalovirus, Epstein-Barr virus and hepatitis B/C may further maintain the inflammatory state5-7. Other microbial triggers, like protozoan parasites may contribute to additional inflammation. Thus, in endemic areas, co-infections with malaria and visceral leishmaniasis in HIV patients represent independent causes of intensive immune activation8,9. Moreover, translocation of bacteria or bacterial products across a damaged gut-blood barrier, so called microbial translocation (MT), has been proposed to be one of the most important mechanisms behind the chronic immune activation in HIV infection10.

1

2 BACKGROUND 2.1

HIV CHARACTERISTICS

HIV is a lentivirus within the Retroviridae family, which infects host cells expressing the CD4 receptor, e.g. lymphocytes, monocytes, dendritic and microglia cells. In addition, an interaction with the co-receptors CCR5 or CXCR4 is crucial for viral cell entry11. By using the viral enzymes reverse transcriptase (RT) for generation of double-stranded DNA from the viral RNA templates, followed by integration of this proviral DNA into the human chromosomes by HIV integrase, a viral reservoir is established in the human genome. This persistent reservoir is formed very early during the acute infection in the resting memory CD4+ cells12. Also other cellular reservoirs exist, such as the pool of macrophages and follicular dendritic cells13,14. The viral replication rate is intensive with 1010-11 virions produced every day15, and together with the inborn high error rate of the RT during the DNA synthesis, an enormous viral diversity develops. Two different types, HIV-1 and HIV-2, infect humans and cause HIV related disease followed by AIDS, if untreated, when the function of the immune system has become severely deteriorated. HIV-1 is phylogenetically classified into several groups: (I) the worldwide spread M (major) group, representing >90% of all HIV infections, which ca be further subdivided into 9 subtypes (A-D, F-H, J, K) and circulating recombinant forms (CRFs); (II) N; (III) O and (IV) P. Also unique recombinant forms exist16. HIV-2 is categorized into groups A-H17,18. The clinical course varies between the two HIV types. Typically, AIDS defining conditions and complications related to HIV-1 infection present 8-10 years after transmission, but a smaller proportion of the patients have an accelerated disease progression already after seroconversion over a period of 2-3 years19. The disease progression is slower in HIV-2 infected, and development of low CD4+ T-cell counts complicated by opportunistic infections may be deferred for 20 (-30) years20,21. The plasma HIV-2 load is usually very low or undetectable during the asymptomatic course in these patients22, similar to the HIV-1 infected Elite Controllers who are able to spontaneously maintain viral plasma suppression without ART for decades23. 2.2

EPIDEMIOLOGY

In the 2016 UNAIDS Global AIDS update, an estimated 36.7 million individuals are living with HIV, of whom ~17 million are on ART at the end of 201524. HIV-1 is responsible for most of the global HIV burden. The overall prevalence of HIV-2 infections is low worldwide, and a total of 1-2 million people are expected to be HIV-2 positive. Anyhow, the estimated HIV-2 seroprevalence is 1-5 % in some countries in West Africa, with significant proportions of patients being dually infected with HIV-125,26. In Sweden, the number of diagnosed people living with HIV was 20th of June 2017: 7338,

according to the Swedish InfCare HIV quality assurance registry with 430 newly diagnosed cases in 2016. This corresponds to a prevalence of ~0.07%, which is one of the lowest in Europe27. During the last five years, 15-25% of the newly diagnosed patients contracted HIV in Sweden according to reports from treating physicians. However recent data suggest that at least 20% of migrants are infected after arrival to our country28.

2.3

HIV-1, IMMUNE ACTIVATION AND INFLAMMATION

HIV-1 infection is associated with activation of both the innate and adaptive parts of the immune system. An extensive systemic immune activation starts immediately at acute infection29, but gradually decreases during the chronic phase, though still present at abnormally high levels30,31. Even in well treated patients with undetectable plasma viral load, a chronic immune activation and low-grade inflammation are found32.

Figure 1. Factors associated with immune activation during HIV-1 infection

Several components of the innate immune system are activated in HIV-1 infection. The myeloid dentritic cells (mDCs), presenting processed antigens to T-cells in lymph nodes with subsequent T-cell activation, as well as interferon-γ producing plasmacytoid dendritic cells (pDCs) display transcriptional profiles associated with immune activation in vivo33. Enteric mDCs become activated by mucosal bacteria like Prevotella, which may lead to both local and systemic immune activation34. Activation of monocytes/macrophages is represented by 3

increased systemic levels of sCD14, sCD16335-37 and inflammatory cytokines (TNF-α, interleukin (IL)-1 and IL-6)38,39. Also the neutrophils are activated with high surface expression of program death ligand 1 (PD-L1), and with upregulation of TNF-α and IL-6 production40,41. Furthermore, overexpression of activation markers on natural killer (NK) cells with reduced cytolytic capacity has been reported in HIV-1 infection42. The cellular immune activation during HIV-1 infection has been extensively explored, and Tcell activation markers may predict disease progression in untreated patients43. Persistent activation of CD4+ and particularly CD8+ T-lymphocytes is evident in the vast majority of naive patients4,30. Common cellular markers of immune activation include surface expression of HLA-DR and CD38. The CD4/8 T-cell ratio is also a useful tool for indirect prediction of immune activation44. The magnitude of CD8+ T-cell immune activation early during HIV-1 infection may predict the CD4+ cell decline independent of the viral load45. It has been assumed, that most CD4+ T-cells will undergo apoptosis secondary to exhaustion and senescence caused by the activation46. ART partially reverses this process, but does not fully restore the CD4+ T-cell dysregulation and function47. Recently, another mechanism behind loss of CD4+ T-cells has been elucidated. Depletion of these cells by pyroptosis, a process where the pool of resting CD4+ cells (~95% of the CD4+ T-lymphocytes) die by caspase-1 programmed cell death seems to be the major cause behind the loss of CD+ T-cells in HIV-1 infection48. This way of cell death is associated with release of pro-inflammatory cytokines like IL-1ß, resulting in an intensive inflammatory reaction. The pyroptosis takes place mainly in lymphoid tissue, and CD4+ T-cells in blood seems to be highly resistant to this type of cell death49. Development of liver fibrosis has been associated with this pathway of cell death50, and the fibrosis in lymphatic tissues observed in HIV-1 infection may be related to this type of inflammatory cell death. Defects in the B-lymphocyte line may further fuel the inflammation in HIV-1 infection. Memory B-cells have a lower quality of response to HIV in infected subjects51, and also decreased IgA and IgG responses have been demonstrated52. HIV-specific antibody responses are improved by ART, but the overall frequencies of HIV-specific B cells remain abnormally low51. Increased activity in the kynurenine pathway of tryptophan catabolism, mediated by the enzyme indoleamine 2,3-dioxygenase 1 (IDO1), has been considered to be another important factor behind the chronic inflammation in HIV infection. IDO1 overactivity in HIV-infection may influence the ratio between gut resident T-regs and Th17+ cells53. This leads to a progressive injury of the epithelial mucosal barrier, followed by increased MT and immune activation54. The chronic immune activation causes a low grade inflammation that persists after initiation of ART, and several soluble systemic markers of inflammation are elevated. Typically, increase of CRP, IL-1, IL-6 and TNF-α is observed. Additionally, the coagulation system is

disturbed with elevated levels of D-dimer, tissue factor and von Willebrand factor. The alternations in the inflammation and coagulation cascades contribute to the HIV related complications from the cardiovascular system, musculoskeletal system, end-organ disease in e.g. liver and kidney, malignancies, neurocognitive impairment and accelerated aging2. 2.4

MICROBIAL TRANSLOCATION

The human gut compartment represents the largest lymphoid organ in the body, and the intestinal mucosa is constantly exposed to external microorganisms. It plays an important role for maintaining the immunological homeostasis, mediated through innate and acquired immunological responses55. Gut associated lymphoid tissue (GALT) consists of mesenteric lymph nodes, Peyer´s patches in the small intestine, and follicular aggregates in the large intestine56. The mucus layer in the gastrointestinal (GI) tract, consisting of proteins, phospholipids, electrolytes, water, secretory IgA and antimicrobial peptides, forms a physiological barrier against pathogenic microorganisms. Intraluminal granulocytes maintain control from commensal bacterial overgrowth, and submucosal macrophages and lymphocytes eliminate bacteria or bacterial products crossing the structural parts of the intestinal wall. This is based upon lined enterocytes, closely connected with tight junctions (intercellular structures that join GI-epithelial cells firmly together). All these parts form a complex construction, termed the gut-blood barrier. It strictly regulates both passive and active transfer of fluid, nutrients and electrolytes. In HIV-1 infection, most of the different anatomical and physiological parts of the gut-blood barrier are abnormal, as reviewed by Sandler and Douek57. The term microbial translocation (MT) refers to translocation of gut resident intraluminal commensal microbial products into systemic circulation without manifest bacteremia. Translocating microbial compounds from bacteria include peptidoglycans from the cell wall58, lipopolysaccharide (LPS) from the outer cell membrane of gram-negative bacteria10, flagellin59,60 and bacterial DNA61. Also viral RNA/DNA62 and ß-glucans from bacterial or fungal organisms may cross the blood-gut barrier63. MT has been linked to a spectrum of diseases besides HIV. It has been described e.g. in patients with inflammatory bowel disease (IBD)64, coeliac disease65, infectious and alcoholic cirrhosis66-68, hepatitis B/C virus infection66,69, and during Dengue infection70. Diseases that are characterized by systemic MT are often associated with shifts in the gut microbiota composition. 2.5

MARKERS OF MICROBIAL TRANSLOCATION

There are numerous established markers of MT. Anyhow, to find appropriate tools and markers to estimate the magnitude of MT has been associated with several difficulties. The traditionally most widely used marker is LPS, a major component of the monolayer of outer cell membrane in most gram-negative bacteria. Thus, it is a direct marker of bacterial products translocating to the systemic circulation. The structure of LPS varies between different bacteria, and the innate immune response may differ 100-fold depending on type of bacterial trigger. LPS forms a complex with LPS-binding protein (LBP), membrane

5

associated or soluble CD14, MD-2 and toll-like receptor 4 (TLR4) on the surface of innate immune cells, preferentially monocytes and macrophages. This starts a cascade of intracellular processes, mediated via several pathways, whereof activation of the transcription factors nuclear factor kappaB (NFκB) and activator protein-1 (AP-1) are the most important71. The subsequent gene expression results in production of inflammatory cytokines like interleukins, TNF-α and interferons72,73 (Figure 2).

Figure 2. LPS/TLR4 complex related intracellular signaling pathways. Adapted from: Scavenger receptor SREC-I mediated entry of TLR4 into lipid microdomains and triggered inflammatory cytokine release in RAW 264.7 cells upon LPS activation. Murshid A, Gong J, Prince T, Borges TJ, Calderwood SK.PLoS One. 2015 Apr 2;10(4):e0122529. doi: 10.1371/journal.pone.0122529. eCollection 2015.

Although LPS has been considered to be the most established marker of MT, the analysis process of this marker is associated with technical issues. There is variability between different limulus lysate assay test kits (standard for LPS detection), but also inter-run variability lowers the validity of results. Additionally, the non-fasting condition at sampling can affect LPS levels, and endogenous circulating proteins may inhibit or degrade systemic LPS. Another direct marker of MT is systemic bacterial DNA. Traditionally, plasma PCR of the conserved 16S ribosomal DNA (16SrDNA) region with Sanger sequencing has been used. Anyhow, the sensitivity and specificity of the method are uncertain with some studies

showing elevated levels of 16SrDNA in HIV positive compared to negative individuals61,74, in opposite to others75,76. Utilizing next generation sequencing (NGS) for characterization of systemic bacterial DNA may enhance the diagnostic accuracy, as discussed by Svärd et al76. Several indirect markers of MT are used. LPS-binding protein (LBP) is an acute phase protein, mainly produced in liver and to a smaller extent in pulmonary, gastrointestinal and kidney epithelial cells77-79. It is mostly released upon LPS stimuli, but induction may also be triggered by other microbiological structures. Peptidoglycans from gram-positive bacteria and β-glucans from fungal organisms are molecules also recognized as LBP inducers80. Membrane bound CD14 is a pattern recognition receptor found mainly on macrophages, recognizing LPS from gram-negative bacteria, peptidoglycans and lipoteichoic acid from gram-positive bacteria, and lipoproteins from spirochetes81. Shedding of the membrane bound CD14 gives the soluble form sCD14, which acts as a marker of monocyte activation upon mainly LPS stimuli, thus appropriate as an indirect marker of MT. Anyhow, HIV itself and a broad spectrum of other microbial agents like Dengue, RSV, and Mycobacteria are known triggers of sCD14 production, which has to be considered when interpreting sCD14 results70,82,83. Intestinal fatty acid binding protein (I-FABP) is released by enterocytes undergoing cell death, and elevated levels reflect damage to the small intestinal cells. As the enterocytes have a high turnover rate, high plasma I-FABP levels indicate an elevated loss of enterocytes followed by abnormally high intestinal permeability84. Elevated levels of I-FABP have been linked to inflammatory bowel diseases, septicemia and also following abdominal surgery85,86. Detection of antibody responses against the bacterial antigen flagellin has been studied in patients with IBD (anti-CBir1)87 and in patients with HIV/AIDS (anti-CBir1, anti-flagellin antibodies)88,89. Both antibodies are of IgG type, and may provide insights of the degree of MT over a prolonged period of time due to their long half-lifetime.

2.6

MICROBIAL TRANSLOCATION IN HIV-1 INFECTION

A rapid depletion of mucosal CD4+ T-cells, preferentially affecting the subpopulation of Th17+ T-cells (Th17) in GALT, starts very early after acquisition of HIV90. The IL-17 and IL-22 producing Th17 cells have essential immunological properties, and are important for the homeostasis of epithelial cells. They produce antimicrobial peptides like defensins, support recruitment of neutrophils on response to intraluminal pathogenic bacteria and fungi, and enhance proliferation of enterocytes91-94. Furthermore, the structural integrity of the barrier in GI-tract is impaired due to the HIV infection, leading to a disruption of the epithelial barrier. This is caused by an increased turnover rate of enterocytes and destruction of the important tight junctions starting within the first weeks post-infection95. Following oral challenge with lactulose/L-rhamnose, an

7

increased urine excretion was observed in 20% of asymptomatic HIV patients, and in vast majority of AIDS patients, reflecting the enhanced intestinal permeability96. In the early HIVera, villous atrophy was observed in patients with wasting syndrome97, with subsequent malabsorption of carbohydrates, proteins, fat and nutrients such as zink and iron. Abnormally low intraluminal IgA-concentrations due to B-cell dysfunction with decreased proportion of mucosal plasma cells has been associated to HIV infection98. Secretory IgA prohibits intraluminal microbes from attachment to and translocation across the epithelial barrier. The local IgA-deficiency may further contribute to less capacity of neutralizing microbial products (Figure 3).

Figure 3. The pathogenesis of HIV-1 induced gut damage. During HIV-1 infection, CD4+ T-cells are lost, and CD8+ T-cells are activated in the submucosal parts of the gut. This is associated with an increased turnover of enterocytes, loss of tight junctions (connecting the epithelial cells strictly together), impaired recruitment of neutrophils and less production of antimicrobial peptides. Additionally, the Blymphocytes are dysfunctional, and intraluminal IgA concentration is lowered. As a consequence, microbial parts may translocate from gut lumen into systemic circulation, triggering the immune system and contributing to chronic immune activation.

The clearance of MT products from systemic circulation takes place mainly in the liver, delivered via the portal vein. Hepatocytes and specialized liver resident macrophages, (Kupffer cells), which are activated by an innate immune response via TLR4-CD14 complex upon LPS-stimuli, clear most of enteric derived LPS99. Kupffer cells are depleted in HIVhepatitis C co-infection100, and serum markers of MT have been elevated compared to hepatitis C mono- infected101. These data suggest that MT may play an important role in the more rapidly developed fibrosis progress and cirrhosis observed in co-infected patients. Phagocytosis by mucosal macrophages is another crucial mechanism to clear translocating microbial products. In a study of simian immunodeficiency virus (SIV) infected rhesus macaques, Estes et al95 showed that intestinal macrophages have impaired phagocytic capability, and instead a dysfunctional response on translocating bacterial products is observed, with secretion of inflammatory cytokines. Similar findings have been reported in HIV infected patients, where density of mucosal macrophages was higher, but their

phagocytic skills were impaired102. Altogether, these defective compounds involved in human defense against microbial products invading from the intestinal lumen contribute to the leakygut syndrome featuring HIV infection. 2.7

MICROBIAL TRANSLOCATION AND ANTIRETROVIRAL THERAPY

ART reduces markers of systemic T-cell activation, but there are conflicting data about the effect on MT. The choice of surrogate MT marker will most likely impact the interpretation of the magnitude of MT. Also co-morbidities, nadir CD4+ cell count, timing and duration of ART may influence level of MT after initiation of ART. Moreover, concomitant use of antibiotics probably may influence some of MT markers, e.g. LPS, LBP and sCD14. Most studies report declining LPS levels after ART initiation10,103,104, while no reduction was observed in other studies35,105-107. This may partly be explained by the different techniques and kits used for determination of the LPS levels, with associated difficulties of measuring LPS. Anyhow, when the more stable marker sCD14 is used, results are still diverging, with some presenting declining35,105,108 or increasing levels104,106 after introduction of ART. The trend is the same for most of the other surrogate markers, with the exception of LBP, that seems to decline in most of the studied HIV cohorts after starting ART109,110. Two studies on early initiation of ART during acute HIV infection did not demonstrate any positive effect on levels of MT markers111,112, although this might be due to that ART was started before any significant MT had developed . Such an interpretation is supported by a recent article, where the introduction of ART during acute HIV infection was associated with less immune activation and inflammation in colonic lamina propria at 24 weeks. Though, a significant reconstitution of CD4+ T-cells was observed in only blood and not in the sigmoid biopsies even after 96 weeks113. These data illustrate the difficulties of interpreting how organ-specific and systemic immune destruction and recovery are connected with inflammation and immune activation related to MT. The impact of the individual components in an HIV drug regimen is less explored. Some minor differences in the levels of monocyte activation markers have been observed, with higher sCD14 in patients on NNRTI + boosted protease inhibitors (PI), but without affecting the overall magnitude of MT114 . Interestingly, monotherapy with PI has also been linked to higher levels of monocyte activation markers (sCD14, sCD163), but still levels of LBP did not diverge from patients with standard ART, thus not indicating increased MT, so other mechanisms than MT may trigger the innate immune activation during PI monotherapy 115. In another cross-sectional study from Mexico, it was reported that the levels of sCD14 and IFABP were elevated in patients on long-term ART based on boosted atazanavir or lopinavir, but not in efavirenz treated subjects116. All together, these findings raise concerns about the insufficient effects of monotherapy with protease inhibitors. In contrast, viral reservoirs were found to be smaller in patients on NNRTI based ART117, and the size of the gut reservoir has been linked to MT118. To summarize, the effect of specific ART regimens and the individual drugs on MT during chronic HIV infection is uncertain, and has to be further investigated in larger scaled, preferable randomized studies.

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2.8

THE HUMAN GUT MICROBIOTA

The total bacterial number in the adult human gut has traditionally been estimated to be ~1014, composed by 500-1000 different species, together creating an estimated biomass of 1.5 kg119,120. The vast majority of the commensal bacteria in the gut resides in the colon, and only small fractions are located in the stomach and the small intestine. Though, in a recent paper the number of enteric bacteria was calculated to be ~4x1013, suggesting that the commonly accepted bacteria to human cell ratio 10:1 is much closer 1:1121. Bacteroides, Clostridium, Lactobacillus, Fusobacterium, Bifidobacterium, Eubacterium, Peptococcus, Peptostreptococcus, Escherichia, and Veillonella are the most abundant genera forming the commensal gut flora122. The human gut microbiome has many crucial biological functions. This bacterial compound facilitates absorption and digestion of nutrients, and also biosynthesizes vitamins like biotin, thiamine and folate. Short-chain fatty acids (SCFA), such as butyrate, propionate and acetate, are of major importance for maintaining the gut homeostasis as they serve as both energy sources for endothelial cells and as signaling molecules123. They are produced by commensal Clostridia and Lactobacillales species , as products of fermentation of dietary fibers and end products from carbohydrates124. Additionally, the microbiome also confers resistance against invasion of pathogenic bacteria, and interferes with the host’s production of antimicrobial peptides. Importantly, it is also deeply involved in development and modulation of the immune system125. Early in life, gut colonization with lactobacilli during first two months after birth has been associated with a favorable cytokine pattern at the age of two years, suggesting that specific bacterial species may affect subsets of T helper cells126.

2.9

GUT MICROBIOTA IN HIV-1 INFECTION

The influence of HIV infection on gut microbial flora was first elucidated in 2008 when the composition of gut microbiome was assessed by fluorescence in situ hybridization and quantitative real-time PCR for Pseudomonas on fecal samples from 57 asymptomatic and ART naïve HIV patients. The presence of Pseudomonas aeruginosa was 92% in HIV infected vs 20% in healthy subjects, corresponding to a 10-fold increase of the Pseudomonas proportion of total microbiota. Further, Candida albicans was detected in all samples from the HIV infected, compared to 40% from the healthy population127, advocating a pathological shift in the composition of the microbial gut flora during HIV infection. Determination of gut microbiome with quantitative molecular techniques was first presented in a pilot study by Ellis et al, demonstrating that total bacterial load analyzed by 16SrDNA PCR was lower and the proportion of order Enterobacteriales was higher in stools of treatment naïve HIV infected compared to uninfected individuals. Additionally, the CD4+ cell count in duodenal tissue correlated negatively with the fraction of Enterobacteriales, and the total bacterial load was also negatively correlated to activation of CD4/8+ cells in duodenal tissue128, highlighting the importance of the gut microbiome composition as a functional trigger of chronic systemic immune activation. Since then, several studies using NGS have shown a

higher abundance of Proteobacteria and depletion of Firmicutes at phylum level in HIV+ populations129-131. More frequently, enrichment of genus Prevotella and depletion of Bacteroides has been reported in fecal samples132,133 or gut mucosal tissue130,134 of untreated chronically HIV infected subjects. Multiple bacterial species involved in production of shortchain fatty acids, e.g. butyrate, are less represented in the fecal flora of HIV+ subjects. Proportions of Faecalibacterium spp, Eubacterium spp. and Coprucoccus spp. have been reduced in several cohorts130,134,135. This may influence the turnover of epithelial cells, and affect the tuning of immunological mucosal cells. In the complex interplay between intraluminal microorganisms and GALT, beneficial commensals like Lactobacillales and Bifidobacteria have been linked to mucosal anti-inflammatory properties136. The relative amount of both species is lowered in fecal flora from an HIV infected population127,134, and dietary supplementation with prebiotics has been shown to partially restore the shortage of both species137. In a randomized trial comparing ART plus maraviroc versus placebo, the systemic and gut CD4+ cell counts were positively correlated to the rectal proportions of Lactobacillales. Additionally, higher proportions of Lactobacillales were associated with less MT in these treatment naïve patients, further indicating the protective qualities of these bacteria. In this longitudinal study, subjects were followed after initiation of ART, and the percentage of gut CD4+ cells correlated to the proportions of Lactobacillales after 48 weeks138, indicating that recovery of the immune system may be due to the interaction between ART and the fraction of beneficial commensals. According to a recent exploratory work by Dinh et al, where the fecal microbiota from 21 HIV patients on suppressive ART for in median 13 years was profiled, the composition differed significantly from healthy controls. Enrichment of Proteobacteria, Gammaproteobacteria, Enterobacteriales, Enterobacteriaceae, Erysipelotrichi, Erysipelotrichales, Erysipelotrichaceae and Barnesiella was found in HIV+ individuals139, and the abundance of pathogenic organisms correlated to markers of MT and systemic inflammation. Thus, dysbiosis of gut microbiota with related MT and immune activation seems to persist for more than a decade even with fully suppressive ART, but supplementation with pre/probiotics may be possible therapeutic strategies. The choice of ART regimen may also be of importance, as only a combination of 2 NRTIs + integrase inhibitor was able to restore the diversity loss and systemic inflammation in a cross-sectional study on HIV-1 patients. But still, in this work no major shifts in the gut microbiome were observed at phylum level before or after initiation of ART114. 2.10 ELITE CONTROLLERS Elite controllers (ECs) constitute a unique subset of HIV-1 infected individuals with the ability to spontaneously control the HIV-1 replication over time without ART, representing less than 1% of the total HIV-1 population23. Until today, there has been sparse data about MT in this group of HIV-1 patients. In the pioneering work by Brenchley et al, ECs demonstrated higher levels of LPS compared to uninfected controls, but levels tended to be lower than in the HIV-1 progressors10. This finding was confirmed by Hunt et al, who investigated 30 ECs, and found that the proportion of activated (CD38+ HLA-DR+) CD4+ and CD8+ cells were higher compared to both HIV-1 negative individuals and patients 11

virologically suppressed by ART. The plasma LPS levels were also significantly elevated in ECs compared to HIV negative controls, consistent with gut MT140. Later on, the number and proportion of CD17+ T-cells in gut biopsies from ECs have been shown to be similar to HIV1 negative individuals141. In a recent study from Kim et al142, four ECs with a median duration of HIV-1 infection for 18.5 years did have similar plasma levels of LPS and sCD14 at baseline as HIV negative controls, thus without evidence of increased MT in these ECs. The blood CD8 T-cell activation was also similar in both groups, but the CD4/CD8 ratio was lower in ECs compared to HIV negative controls, and higher levels of D-dimer and IL-6 were observed in ECs. All ECs received ART for 6 months, but did not normalize their levels; nevertheless CD4/CD8 ratio was positively affected. Interestingly, a reduction of the mucosal Th17+ cell polyfunctionality was observed after ART discontinuation, but no long-term follow up of MT was performed in order to search for a progressive MT. In a Brazilian cohort, 7 ECs and HIV negative controls were found to have comparable sCD14 levels, but in ECs with occasional viremic episodes (3)-beta-D-glucan levels in HIV-infected individuals are associated with immunosuppression, inflammation, and cardiopulmonary function. Journal of acquired immune deficiency syndromes. Dec 01 2012;61(4):462-468.

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Kinetics of Microbial Translocation Markers in Patients on Efavirenz or Lopinavir/r Based Antiretroviral Therapy Jan Vesterbacka1*, Piotr Nowak1,2, Babilonia Barqasho2, Samir Abdurahman1, Jessica Nystro¨m2, Staffan Nilsson3, Hiroyuki Funaoka4, Tatsuo Kanda5, Lars-Magnus Andersson6, Magnus Gissle`n6, Anders So¨nnerborg1,2 1 Unit of Infectious Diseases, Department of Medicine, Karolinska Institutet, Karolinska University Hospital, Huddinge, Stockholm, Sweden, 2 Department of Laboratory Medicine, Division of Clinical Microbiology, Karolinska Institutet, Karolinska University Hospital, Huddinge, Stockholm, Sweden, 3 Department of Mathematical Statistics, Chalmers University of Technology, Gothenburg, Sweden, 4 DS Pharma Biomedical Company, Limited, Osaka, Japan, 5 Division of Digestive and General Surgery, Niigata University Graduate School of Medical and Dental Science, Niigata, Japan, 6 Department of Infectious Diseases, University of Gothenburg, Gothenburg, Sweden

Abstract Objectives: We investigated whether there are differences in the effects on microbial translocation (MT) and enterocyte damage by different antiretroviral therapy (ART) regimens after 1.5 years and whether antibiotic use has impact on MT. In a randomized clinical trial (NCT01445223) on first line ART, patients started either lopinavir/r (LPV/r) (n = 34) or efavirenz (EFV) containing ART (n = 37). Lipopolysaccharide (LPS), sCD14, anti-flagellin antibodies and intestinal fatty acid binding protein (I-FABP) levels were determined in plasma at baseline (BL) and week 72 (w72). Results: The levels of LPS and sCD14 were reduced from BL to w72 (157.5 pg/ml vs. 140.0 pg/ml, p = 0.0003; 3.13 ug/ml vs. 2.85 ug/ml, p = 0.005, respectively). The levels of anti-flagellin antibodies had decreased at w72 (0.35 vs 0.31 [OD]; p,0.0004), although significantly only in the LPV/r arm. I-FABP levels increased at w72 (2.26 ng/ml vs 3.13 ng/ml; p,0.0001), although significantly in EFV treated patients only. Patients given antibiotics at BL had lower sCD14 levels at w72 as revealed by ANCOVA compared to those who did not receive (D = 20.47 mg/ml; p = 0.015). Conclusions: Markers of MT and enterocyte damage are elevated in untreated HIV-1 infected patients. Long-term ART reduces the levels, except for I-FABP which role as a marker of MT is questionable in ART-experienced patients. Why the enterocyte damage seems to persist remains to be established. Also antibiotic usage may influence the kinetics of the markers of MT. Trial Registration: ClinicalTrials.gov NCT01445223 http//clinicaltrials.gov/ct2/show/NCT01445223?term = NCT01445223 Citation: Vesterbacka J, Nowak P, Barqasho B, Abdurahman S, Nystro¨m J, et al. (2013) Kinetics of Microbial Translocation Markers in Patients on Efavirenz or Lopinavir/r Based Antiretroviral Therapy. PLoS ONE 8(1): e55038. doi:10.1371/journal.pone.0055038 Editor: Alan Landay, Rush University, United States of America Received September 4, 2012; Accepted December 18, 2012; Published January 28, 2013 Copyright: ß 2013 Vesterbacka et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Funding: This work was supported by the Swedish Research Council, Stockholm County Council, Swedish Physicians against AIDS, Swedish Medical Society (SLS), Swedish Society for Medical Research (SSMF for Piotr Nowak), Sahlgrenska Academy at University of Gothenburg and The Health & Medical Care Committee of the Region Va¨stra Go¨taland. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing Interests: The authors do not have a commercial or other association that might pose a conflict of interest with the exception of Dr HF is employed by DS Pharma Biomedical Co., Ltd, the company that developed a kit for I-FABP. This does not alter the authors’ adherence to all the PLOS ONE policies on sharing data and materials. * E-mail: [email protected]

immune activation may contribute to the low-grade viremia and e.g. cardiovascular and CNS complications [7,8,9]. Several markers are used to assess microbial translocation (MT) in patients with HIV or inflammatory bowel disease [10], such as microbial products [lipopolysaccharide (LPS), plasma bacterial 16SrDNA, anti-flagellin antibodies] [11], markers of the systemic response to bacterial products (sCD14, LPS-binding protein), and of enterocyte damage [intestinal fatty acid binding protein (IFABP)] [12,13]. During successful ART, MT and systemic immune activation are usually reduced, but not normalized, suggesting that the damage of the gut-blood barrier is only partly restored [5]. The reasons why this improvement varies between patients are not known. The origin of low-level viremia in patients on suppressive ART has been disputed. Residual virus replication from anatomical

Introduction A sustained control of the human immunodeficiency virus type 1 (HIV-1) replication is obtained by antiretroviral therapy (ART) in the majority of patients, reducing plasma HIV-1 load to undetectable levels. However, HIV-1 persists in reservoirs like latently infected CD4+ T cells [1,2] and in body compartments that have restricted permission for antiretroviral drugs. It is hypothesized that these reservoirs are refilled by the low grade viral replication seen in patients on suppressive ART who otherwise have undetectable viremia by routine assays [3,4]. Translocation of bacterial products across a damaged gut-blood barrier has been proposed to be one important mechanism for the persistence of a chronic immune activation which is found also in well-treated patients [5,6]. There is growing evidence that this PLOS ONE | www.plosone.org

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compartments like the gut could be one of the explanations. Firstly, levels of HIV-1 DNA and RNA were substantially elevated in the gut compared with peripheral blood in patients on ART with ,40 HIV-1 RNA copies/ml, indicating that the gut may serve as a potential source of viremia during suppressive ART [14]. Additionally, in a set of patients on long-term ART, levels of HIV DNA in sigmoid colon were positively correlated to plasma LPS levels [15], suggesting a connection between residual viremia and MT. In a cross-sectional study of patients with persistently undetectable HIV-1 RNA, a higher proportion of participants treated with nevirapine and efavirenz achieved ,2.5 HIV-1 RNA copies/ml compared to lopinavir/r based ART [16]. Given the link between MT and low-level viremia, we assumed that choice of ART could differently affect kinetics of MT markers. In the present study, we analyzed the levels of LPS, sCD14, IFABP, and anti-flagellin antibodies, at baseline (BL) and after 72 weeks (w72) of ART in a controlled randomized clinical trial in which the patients received either lopinavir/r +2 nucleoside analogues (NRTI) or efavirenz +2 NRTI. Additionally, we studied if ongoing antibiotics treatment had an impact on the explored parameters.

levels were determined by enzyme-linked immunosorbent assays (R&D Systems, USA and DS Pharma Biomedical Co, Japan; respectively), according to the manufacturers instructions [19]. Samples at BL and w72 from the same patient were assayed on the same plate. Antibody titers to flagellin, and total IgG levels were assessed by an in-house anti-flagellin specific IgG ELISA [20] using purified flagellin monomers from S. typhimurium (InvivoGen, USA). It is known that human sera have a similar recognition pattern of flagellin monomers whether isolated from flagellated E. coli or S. typhimurium [21]. Briefly, microwell plates (MWP) were coated overnight with purified flagellin from S. typhimurium (25 ng/well). The following day, plasma samples from HIV-1 patients were diluted 1:1000 and applied to the MWP. After incubation and washing, the MWPs were incubated with HRP-conjugated antihuman IgG. For total IgG ELISA, the manufacturer’s procedure was followed (MABTECH, Nacka, Sweden).

Statistical Analysis Data were analyzed using GraphPad Prism v. 5.02 and R 2.13.1. Independent groups were compared using Mann-Whitney U-test and paired data analyzed with Wilcoxon signed rank test. Correlations were analyzed by Spearmans rank test. Differences in LPS, sCD14, I-FABP and anti-flagellin IgG levels between patients with or without antibiotics were analyzed with ANCOVA using covariates age, sex, log viral load and CD4+ T-cell count at BL or w72, and residual plots were inspected. Model selection was done by backward elimination with removal of variables if P.0.1.

Methods Subjects During 2004–2007, 239 HIV-1 infected subjects received allocated intervention after written consent in a Scandinavian randomized clinical phase IV efficacy trial (RCT) (ClinicalTrials.gov identifier: NCT01445223). The protocol for this trial and supporting CONSORT checklist are available as supporting information; see Checklist S1 and Protocol S1. The study protocol was approved by the Regional Ethics Committee (Gothenburg ¨ 739-03). The study design and participants have been described O elsewhere [17,18]. In our substudy, the patients were randomized to receive either efavirenz (EFV) +2 NRTI once daily (n = 37) or ritonavir-boosted lopinavir (LPV/r) +2 NRTI twice daily (n = 34) (Figure 1). Totally 59 patients were excluded from our analysis because of insufficient remaining plasma volumes after the main study analyzes. CD4+ T-cell count, viral load (VL), rate of hepatitis B/C co-infection and age were similar in the group of excluded patients at BL, compared to the substudy group. Data on antibiotic therapy was available in 63 patients of whom 29 were given antibiotics at baseline (BL) (n = 27) and/or week72 (w72) (n = 10), while 34 had not received antibiotics at any of the two time points (Table 1). At BL, the patients received: cotrimoxazole (TMP-SMX) as Pneumocystis jiroveci prophylaxis (PCP) (n = 24) or for treatment of pneumonia (n = 2), or clindamycin (n = 1). Also, two were on Mycobacterium tuberculosis treatment, and one was on fluconazole. At w72, TMP-SMX was given as PCP prophylaxis (n = 9), and one patient received nitrofurantoin; 8 of these 10 had had TMP-SMX at baseline.

Results HIV RNA Load and Recovery of CD4+ T-cells Following initiation of ART, all patients achieved plasma HIVRNA ,50 copies/mL within 24 weeks, except for five patients (all ,250 c/mL). Four of these reached undetectable HIV-RNA at w72. Two patients had a relapse with detectable HIV-RNA at w72 (190 respective 640 c/mL). No statistically significant differences were found at BL or follow-up between the two arms (Table 2). BL CD4+ T-cells in the LPV/r group (median 155 [IQR 119.5– 203.3] cells/ul) and in the EFV group (130 [IQR 69–200] cells/ul) did not differ significantly (Table 2). There was no difference with regard to CD4+ T-cell recovery at w72 (LPV/r: 199 [IQR 135– 294]; EFV: 156 [IQR 90–270]) or w48 (p = 0.27) (data not shown). At w72 the CD4+ T-cell count tended to be higher in the LPV/r group as compared to the EFV group (data not shown). There was no correlation between change in CD4+ T-cells and change of any of the markers between BL and w72.

Decrease of LPS and sCD14 after 72 Weeks of ART The overall plasma levels of LPS were reduced at w72 compared to BL (157.5 pg/ml [IQR 128.2–171.1] vs. 140.0 [IQR 127.8–155.2]; p = 0.0003) (Figure 2). The reduction in LPS levels and absolute change between BL and w72 was similar in both treatment arms (data not shown). No significant correlation was observed between LPS and CD4+ T-cell count, VL, sCD14 or I-FABP, respectively. Similar to LPS, plasma levels of sCD14 were reduced at w72 compared to BL (3.13 ug/ml [IQR 2.7–3.8] vs. 2.85 ug/ml [IQR 2.4–3.4]; p = 0.005) (Figure 3) in both treatment arms. The CD4+ T-cell count and sCD14 levels showed a highly significant negative correlation at BL (r = 20.42, p = 0.0003) (Figure 4A) and at w72 (r = 20.32, p = 0.007). Viral load and sCD14 levels correlated at baseline (r = 0.42, p = 0.0002) (Figure 4B).

CD4+ T-cells and Plasma HIV-1 RNA HIV RNA load and CD4+ T-cell counts were measured as part of the clinical routine with Cobas Amplicor (Roche Molecular Systems Inc., Branchburg, New Jersey, USA), and flow cytometry, respectively.

Microbial Translocation Markers Plasma samples obtained at the sampling day were frozen at 280uC and later thawed. The analyses were performed blindly in relation to clinical data and treatment outcome. Levels of LPS were measured by limulus amebocyte assay (LAL, Lonza, Maryland, USA) as previously described [5]. sCD14 and I-FABP PLOS ONE | www.plosone.org

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Figure 1. Trial profile and reasons for discontinuations in each group. doi:10.1371/journal.pone.0055038.g001

0.22–0.61] at BL vs. 0.31 [IQR 0.21–0.5]) at w72; p = 0.0004) (Figure 6). In the LPV/r arm, anti-flagellin antibodies decreased significantly (median OD 0.34 [IQR 0.22–0.5] vs. 0.25 [IQR 0.14–0.49]; p = 0.001), but not in the EFV treated patients (median OD 0.35 [IQR 0.23–0.63] vs. 0.37 [IQR 0.24–0.51]; p = 0.06). As expected, the total IgG concentrations were reduced at w72 (median OD 1.02 [IQR 0.99–1.07] at BL vs 0.99 [IQR 0.96–1.02] at w72; p = 0.0001) in the entire cohort, and in both treatment arms (LPV/r arm median OD 1.02 [IQR 0.99–1.05] at BL vs 0.98 [IQR 0.94–1.01] at w72; p,0.0001); (EFV arm median OD 1.03 [IQR 0.98–1.08] at BL vs 1 [IQR 0.96–1.03] at w72; p,0.0001). The anti-flagellin IgG:total IgG ratio was reduced between BL and w72 in whole cohort (median 0.34 [IQR 0.22–0.53] vs 0.3 [IQR 0.21–0.5]; p = 0.005) and LPV/r arm (median 0.34 [IQR 0.22–0.48] vs 0.26 [IQR 0.15–0.47]; p = 0.003), supporting that the decrease of anti-flagellin IgG was specific. This reduction was not observed in EFV treated (median 0.34 [IQR 0.23–0.59] vs 0.37 [IQR 0.25–0.52]; p = 0.31). LPS and anti-flagellin antibodies correlated at BL

Elevated Levels of I-FABP after 72 Weeks of EFV Containing ART At BL, no difference was found in plasma I-FABP levels between the treatment groups. At w72, the overall I-FABP concentrations had increased (median 2.26 ng/ml [IQR 1.4–3.6] at BL vs 3.13 ng/ml [IQR 1.8–4.9] at w72; p,0.0001) (Figure 5). The elevation was significant only in the EFV arm (2.32 [IQR 1.5–3.8] vs. 4.29 [IQR 2.4–5.9]; p,0.0001), but not in the LPV/r arm (2.19 [IQR 1.3–3.4] vs. 2.56 [IQR 1.7–3.5]). The difference in elevation between the two arms was significant (p = 0.035). A significant difference was also found between the treatment arms at w72 (EFV: median 4.29 [IQR 2.4–5.9]; LPV/r: 2.56 [IQR 1.7– 3.5]; p = 0.003). There was no significant correlation between IFABP levels and CD4+ T-cells, VL, and sCD14, respectively.

Decrease of Anti-flagellin Antibodies after 72 Weeks of ART Anti-flagellin antibodies were detected in all subjects. ART reduced the levels in the whole cohort (median OD 0.35 [IQR Table 1. Baseline characteristics of antibiotic treated patients.

All

Antibiotic treated

Other

Subjects [number]

63

27

36

CD4+ count/ul [median (range)]

160 (90–205)

120 (30–150)

180 (138–220)

HIV-1 RNA [median log10 copies/ml (range)]

5.25 (2.95–7.07)

5.34 (3.86–7.07)

5.15 (2.95–6.66)

doi:10.1371/journal.pone.0055038.t001

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Table 2. Characteristics of HIV-1 infected patients.

All

Lopinavir-arm*

Efavirenz-arm*

Subjects [number]

71

34

37

Age [years, median (range)]

37 (19–70)

41 (19–68)

35 (20–70)

Sex [male/female]

51/20

24/10

27/10

Hepatitis [B/C]

1/3

1/2

0/1

130 (0–270)

CD4+ count/ul [median (range)] BL

140 (0–370)

155 (11–370)

w72

330 (73–1260)

370 (160–1260)

BL

5.3 (2.95–7.07)

5.3 (2.95–6.72)

5.3 (3.23–7.07)

w72

0 (0–2.81)

0 (0–2.28)

0 (0–2.81)

BL

27

10

17

w72

10

3

7

300 (73–843)

HIV-1 RNA [median log10copies/ml (range)]

Antibiotics use1

*There were no statistically significant differences in age, CD4+ -cell count or HIV-1 RNA between the two treatment arms at BL. Abbreviations: BL, baseline. Data from 63 subjects were available. doi:10.1371/journal.pone.0055038.t002 1

(r = 0.25, p = 0.04) and at w72 (r = 0.31, p = 0.01). On the contrary, there was no significant correlation at BL or w72 between anti-flagellin antibodies and CD4+ T-cells, VL, sCD14 or I-FABP, respectively.

Antibiotic Treatment and Markers of Microbial Translocation We explored the impact of antibiotics on markers of MT with three comparisons using ANCOVA adjusting for significant

Figure 2. Levels of LPS. Levels of LPS were significantly reduced after 72 weeks of antiretroviral therapy in the whole cohort, with a unified pattern in both treatment arms. Data are shown as individual values with corresponding baseline LPS levels at X-axis and week 72 levels at Y-axis, respectively. Individuals treated with lopinavir (LPV/r) are indicated with shaded and efavirenz (EFV) with black circles. Dotted lines refer to median values at the corresponding time-point. doi:10.1371/journal.pone.0055038.g002

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Figure 3. Levels of sCD14. Levels of sCD14 were significantly reduced after 72 weeks of antiretroviral therapy in the whole group, with a unified pattern in both treatment arms. Data are shown as individual values with corresponding baseline sCD14 levels at X-axis and week 72 levels at Y-axis, respectively. Individuals treated with lopinavir (LPV/r) are indicated with shaded and efavirenz (EFV) with black circles. Dotted lines refer to median values at the corresponding time-point. doi:10.1371/journal.pone.0055038.g003

antibiotic treated vs untreated patients at BL was then found (median D = 20.85 vs 20.08 mg/ml, p = 0.02) (Figure 7). No effect of antibiotics was observed on the levels of LPS, I-FABP and antiflagellin antibodies, respectively.

covariates. At BL, no difference was found between patients with or without antibiotics. At w72, the levels of sCD14 were lower in patients with ongoing antibiotic treatment vs. those without (D = 20.70 mg/ml, p = 0.017). Also, in the untreated group at w72 the patients who had been treated with antibiotics at baseline had lower levels than those who had been untreated at baseline (D = 20.47 mg/ml; p = 0.015). Finally, the change in the sCD14 levels between BL and w72 was calculated. A difference between

Discussion The microbial translocation (MT) markers assessed in our study (LPS, sCD14, I-FABP, anti-flagellin antibodies) were all increased

Figure 4. Correlations between sCD14, CD4+ T-cells and HIV-1 RNA. At baseline, significant correlations were found between sCD14 and CD4-T cell counts (A) or HIV-1 RNA viral load (B), respectively. Rho and p-value refer to Spearman’s rank test. doi:10.1371/journal.pone.0055038.g004

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Figure 5. Levels of Intestinal Fatty Acid Binding Protein (I-FABP). Plasma levels of I-FABP were significantly elevated after 72 weeks of antiretroviral treatment as compared to baseline in the whole cohort. Stratified to treatment arms, efavirenz (EFV) treated patients had significantly increased levels, but not the patients on lopinavir/r (LPV/r) therapy. Data are shown as individual values with corresponding baseline I-FABP levels at X-axis and week 72 levels at Y-axis, respectively. Individuals treated with lopinavir (LPV/r) are indicated with shaded and efavirenz (EFV) with black circles. Dotted lines refer to median values at the corresponding time-point. doi:10.1371/journal.pone.0055038.g005

in plasma before treatment and ART influenced the levels during the follow-up period of 72 weeks. The reliability of our results is strengthened by the fact that the patients were included in a randomized clinical trial and were followed closely before, during and after the study. Based on the randomization, we found that the effects on the selected MT parameters could partly differ depending on the type of ART and if antibiotics were given or not. We therefore suggest that other factors than HIV treatment in itself may be relevant for the kinetics of the biomarkers which should be considered when interpreting studies on MT in HIV-1 infected patients. Data from our RCT cohort showed that the plasma levels of LPS were significantly reduced after 72 weeks of ART with similar pattern in patients treated with NNRTI or PI/r containing therapy. Similar observations on the decrease of plasma LPS after ART have been reported in some [5,6,22], but not all studies [23,24]. Although, estimating MT by measurement of plasma LPS levels is common, both LAL assay variability as well as patient cohort heterogeneity (e.g. diverse rate of opportunistic conditions or hepatitis co-infection) may lie behind the different results. E.g., in a recent work, the kinetics of MT markers (measured by LPS and sCD14 levels) differed according to the severity of pre-ART CD4+ T-cell count [25]. The effect on sCD14 has also been disputed with studies showing decline [23,26] or increase [22,24] after initiation of ART. In our study, the sCD14 levels were reduced during ART with a unified pattern in the two treatment arms which is in line with a decreased MT during 72 weeks of ART. It has also been PLOS ONE | www.plosone.org

suggested that sCD14 independently predicts mortality in HIV-1 infected patients when adjusting for other key markers [13]. We found a strong inverse correlation between CD4+ T-cells and sCD14 as well as a direct correlation between sCD14 and VL [27]. These findings warrant the hypothesis that higher viral replication is associated with more profound inflammatory response (reflected by sCD14) and leads to lower CD4 T cell counts that also reflect poorer surveillance of gut microbes. The viscous circle of viral replication and inflammation is created and maintained by the ‘‘leaky gut’’ as suggested by Douek et al [28]. One should acknowledge that the sCD14 levels are also elevated in other infections (RSV, Dengue Virus, Mycobacteria) and inflammatory conditions [29,30]. Thus, although analysis of sCD14 is important for the evaluation of MT in the setting of HIV-1 infected patients, it cannot be considered as a specific marker for MT alone. Our untreated patients exhibited elevated plasma levels of IFABP, as compared to historical healthy controls [19], which is in line with the suggestion that I-FABP can be applied as a marker of enterocyte damage and possibly of MT in HIV-1 infected patients [19]. Actually, the levels were similar to those reported in inflammatory bowel disease (IBD) [31], supporting the presence of a significant damage to the enterocytes in HIV-1 patients, at least in those who have a relatively advanced immunodeficiency. To our knowledge, no data on the effect of ART on I-FABP levels have earlier been published. Surprisingly, we found that the IFABP levels increased in the whole cohort despite 72 weeks of efficient ART. A subgroup analysis revealed that the I-FABP increase occurred in the patients treated with EFV, but not in 6

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Figure 6. Plasma levels of anti-flagellin antibodies. A significant reduction of anti-flagellin IgG levels was seen after 72 weeks of antiretroviral treatment compared to baseline in the whole cohort. Plasma levels of anti-flagellin IgG decreased significantly in lopinavir/r (LPV/r) treated patients, but not during efavirenz (EFV) therapy. Data are shown as individual values with corresponding baseline anti-flagellin IgG levels at X-axis and week 72 levels at Y-axis, respectively. Individuals treated with lopinavir (LPV/r) are indicated with shaded and efavirenz (EFV) with black circles. Dotted lines refer to median values at the corresponding time-point. doi:10.1371/journal.pone.0055038.g006

those with LPV/r. This difference between the two treatment arms could not be explained by any coexisting liver failure, gastrointestinal disease (Inflammatory Bowel Disease, gastroenter-

itis) or reported side effects such as diarrhea (data not shown). The finding was unexpected particularly in view of the reports claiming a lower level of the residual viremia in EFV-treated patients as

Figure 7. Change (D) in sCD14 levels in relation to antibiotics. Change (D) in sCD14 levels between baseline (BL) and 72 weeks of treatment (w72). Patients treated with antibiotics at BL had a larger reduction in sCD14 levels at w72 than those who did not receive antibiotics at BL. P-value refers to Mann-Whitney test. doi:10.1371/journal.pone.0055038.g007

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compared to those on a PI/r regimen [16,32,33]. Although IFABP has been firmly described as marker of enterocyte damage in other diseases [34,35], we cannot exclude that the increased IFABP concentrations in our patients might be related to other events such as drug toxicity or metabolic lipid changes. However, the available laboratory blood and lipid-profile data (baseline and follow up) from our patients did not support these relationships (data not shown). Another hypothesis could be based on that EFV may induce oxidative stress related cell apoptosis [36,37]. Conversely, PIs are attributed the anti-apoptotic effect [38,39]. The CD4+ T-cell recovery did not differ significantly between treatment arms, but tended to be higher in LPV/r group. As such, the possibility of immune reconstitution in the gut as a cause of the increasing I-FABP levels in EFV group thus seems to be less likely. Further studies are required to determine if the difference reported by us is related to variation in apoptosis or enhanced turnover of intestinal epithelial cells and as a consequence shedding of I-FABP. In the light of our report, the use of I-FABP for evaluating MT in patients introduced to ART seems questionable, as the kinetics differed compared to the other markers of MT. Most likely the systemic I-FABP levels in patients on ART do not reflect only MT itself. Further studies that include also intestinal biopsies should address these questions. The bacterial flagellin is known as a microbial compound with strong immune modulatory properties that has an essential role in conditions with intestinal damage, like IBD. Hence, flagellin is regarded as a dominant immune antigen in Crohns disease (CD) where the antibodies to bacterial flagellin (Anti-CBir1) are detected in about half of patients [40]. Recently we found elevated levels of flagellin-specific IgG in three cohorts of HIV-1 infected patients [11]. Additionally, two years of ART reduced the levels of anti-flagellin IgG, although they were not normalized [20]. In the present study, we confirm and expand our previous observations. Thus, the baseline anti-flagellin levels were increased in all patients and decreased significantly after 72 weeks of ART. However, stratifying the cohort into the treatment arms showed that the significant decrease occurred in the LPV/r containing arm only. This effect was not due to the general polyclonal B-cells activation as the normalization of specific anti-flagellin antibodies to total IgG levels yielded similar results. Our hypothesis is therefore that the decline of the anti-flagellin antibodies was due to decrease of exposure for flagellin itself, as a consequence of restoration of the gut-blood barrier. We also claim that the positive correlation between anti-flagellin antibodies and LPS supports the credibility of anti-flagellin antibodies as a marker of MT, theoretically being more specific than e.g. sCD14, which is a polyclonal marker in nature [41]. The relevance of the observed difference between treatment arms is not clear. It is thus possible, that since both arms tended to decrease the levels of anti-flagellin antibodies, differences in time kinetics between the arms could possibly result in a faster decline in LPV/r group. Antibiotic treatment leads to changes in the gut microbiota [42,43]. Also, plasma LPS levels are reduced in SIV infected

macaques that are treated with ‘‘gut sterilizing’’ antibiotics [6]. However, so far the impact of antibiotics has not been considered in studies on MT in HIV-1 infected patients. In our study, antibiotic treatment was found to influence the sCD14 levels. ANCOVA-analysis thus revealed that former use of antibiotics at baseline as well as ongoing antibiotic treatment lowered sCD14 levels at week 72 compared to non-antibiotic treated individuals. Additionally, the group using antibiotics at base-line had a larger decrease in sCD14 levels up to week 72. A higher reduction of sCD14 levels in antibiotic treated patients could be due to decreased LPS signaling as a consequence of altered gramnegative intestinal flora. The use of TMP-SMX prophylaxis in ART naı¨ve patients has been associated with a lower annual increase in HIV-1 RNA [44]. Antibiotics like minocycline decrease monocyte activation and can dampen the general inflammation as shown in SIV model [45]. Moreover, rifaximin, a broad-spectrum antibiotic with minimal systematic uptake, has recently been shown to affect endotoxinemia in patients with decompensated cirrhosis. Thus, plasma LPS levels were significantly reduced after 8 weeks course of this antibiotic [46]. These findings together suggest that antibiotic treatment may influence levels of MT markers, potentially providing a bias in studies not compensating for the use. Collectively, we found that markers of MT were reduced after 72 weeks of ART. EFV and LPV/r based ART, which had similar virological outcome, presented with somewhat different effects on the kinetics of MT markers. Thus, although the profiles of the established markers LPS and sCD14 were unified after 72 weeks of treatment, the levels of I-FABP increased and anti-flagellin antibodies were not significantly reduced, respectively, in the patients on EFV containing therapy. Our data underscore the importance of unraveling the multifaceted correlations between microbial translocation, immune activation, antibiotics usage, HIV-1 replication and the chosen ART. Further longitudinal studies should address this complex issue.

Supporting Information Checklist S1 CONSORT Checklist.

(DOC) Protocol S1 Trial Protocol.

(DOC)

Acknowledgments We thank the participants of the NORTHIV trial.

Author Contributions Conceived and designed the experiments: JV, PN, AS, HF, TK, L-MA, MG. Performed the experiments:. BB, SA, JN. Analyzed the data: JV, PN, AS. Wrote the paper: JV, PN, AS.

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antiretroviral therapy: the role of interleukin 7 and interleukin 7 receptor alpha and microbial translocation. J Infect Dis 202: 1254–1264. Marchetti G, Cozzi-Lepri A, Merlini E, Bellistri GM, Castagna A, et al. (2011) Microbial translocation predicts disease progression of HIV-infected antiretroviral-naive patients with high CD4+ cell count. AIDS 25: 1385–1394. Douek DC, Roederer M, Koup RA (2009) Emerging concepts in the immunopathogenesis of AIDS. Annu Rev Med 60: 471–484. Anas A, van der Poll T, de Vos AF (2010) Role of CD14 in lung inflammation and infection. Crit Care 14: 209. Ayaslioglu E, Kalpaklioglu F, Kavut AB, Erturk A, Capan N, et al. (2012) The role of CD14 gene promoter polymorphism in tuberculosis susceptibility. J Microbiol Immunol Infect. Kanda T, Tsukahara A, Ueki K, Sakai Y, Tani T, et al. (2011) Diagnosis of ischemic small bowel disease by measurement of serum intestinal fatty acidbinding protein in patients with acute abdomen: a multicenter, observer-blinded validation study. J Gastroenterol 46: 492–500. Palmisano L, Giuliano M, Nicastri E, Pirillo MF, Andreotti M, et al. (2005) Residual viraemia in subjects with chronic HIV infection and viral load ,50 copies/ml: the impact of highly active antiretroviral therapy. AIDS 19: 1843– 1847. Nicastri E, Palmisano L, Sarmati L, D’Ettorre G, Parisi S, et al. (2008) HIV-1 residual viremia and proviral DNA in patients with suppressed plasma viral load (,400 HIV-RNA cp/ml) during different antiretroviral regimens. Curr HIV Res 6: 261–266. Derikx JP, Vreugdenhil AC, Van den Neucker AM, Grootjans J, van Bijnen AA, et al. (2009) A pilot study on the noninvasive evaluation of intestinal damage in celiac disease using I-FABP and L-FABP. J Clin Gastroenterol 43: 727–733. Wiercinska-Drapalo A, Jaroszewicz J, Siwak E, Pogorzelska J, Prokopowicz D (2008) Intestinal fatty acid binding protein (I-FABP) as a possible biomarker of ileitis in patients with ulcerative colitis. Regul Pept 147: 25–28. Pilon AA, Lum JJ, Sanchez-Dardon J, Phenix BN, Douglas R, et al. (2002) Induction of apoptosis by a nonnucleoside human immunodeficiency virus type 1 reverse transcriptase inhibitor. Antimicrob Agents Chemother 46: 2687–2691. Blas-Garcia A, Esplugues JV, Apostolova N (2011) Twenty years of HIV-1 nonnucleoside reverse transcriptase inhibitors: time to reevaluate their toxicity. Curr Med Chem 18: 2186–2195. Rizza SA, Badley AD (2008) HIV protease inhibitors impact on apoptosis. Med Chem 4: 75–79. Badley AD (2005) In vitro and in vivo effects of HIV protease inhibitors on apoptosis. Cell Death Differ 12 Suppl 1: 924–931. Lodes MJ, Cong Y, Elson CO, Mohamath R, Landers CJ, et al. (2004) Bacterial flagellin is a dominant antigen in Crohn disease. J Clin Invest 113: 1296–1306. Lien E, Aukrust P, Sundan A, Muller F, Froland SS, et al. (1998) Elevated levels of serum-soluble CD14 in human immunodeficiency virus type 1 (HIV-1) infection: correlation to disease progression and clinical events. Blood 92: 2084– 2092. Jakobsson HE, Jernberg C, Andersson AF, Sjolund-Karlsson M, Jansson JK, et al. (2010) Short-term antibiotic treatment has differing long-term impacts on the human throat and gut microbiome. PLoS One 5: e9836. Jernberg C, Lofmark S, Edlund C, Jansson JK (2010) Long-term impacts of antibiotic exposure on the human intestinal microbiota. Microbiology 156: 3216–3223. Mermin J, Lule J, Ekwaru JP, Malamba S, Downing R, et al. (2004) Effect of cotrimoxazole prophylaxis on morbidity, mortality, CD4-cell count, and viral load in HIV infection in rural Uganda. Lancet 364: 1428–1434. Campbell JH, Burdo TH, Autissier P, Bombardier JP, Westmoreland SV, et al. (2011) Minocycline inhibition of monocyte activation correlates with neuronal protection in SIV neuroAIDS. PLoS One 6: e18688. Kalambokis GN, Tsianos EV (2012) Rifaximin reduces endotoxemia and improves liver function and disease severity in patients with decompensated cirrhosis. Hepatology 55: 655–656.

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AIDS RESEARCH AND HUMAN RETROVIRUSES Volume 31, Number 8, 2015 ª Mary Ann Liebert, Inc. DOI: 10.1089/aid.2014.0366

PATHOGENESIS

Effects of Co-Trimoxazole on Microbial Translocation in HIV-1-Infected Patients Initiating Antiretroviral Therapy Jan Vesterbacka,1 Babilonia Barqasho,2 Amanda Ha¨ggblom,1,3 and Piotr Nowak1,2

Abstract

Microbial translocation (MT) contributes to immune activation during HIV-1 infection, and persists after initiation of antiretroviral therapy (ART). We investigated whether levels of MT markers are influenced by the use of co-trimoxazole (TMP-SMX) in HIV-1 patients. Plasma samples were obtained from HIV-1-infected patients initiating ART with (n = 13) or without (n = 13) TMP-SMX prophylaxis. Markers of MT [lipopolysaccharide-binding protein (LBP), lipopolysaccharide (LPS), soluble CD14 (sCD14), and intestinal fatty acid binding protein (I-FABP)] were assessed at baseline (BL), at 1 month, and at 1 year by the Limulus Amebocyte Lysate Assay or ELISA. BL levels of LBP were elevated in both categories of patients; they were highest in patients starting ART and TMP-SMX (median, lg/ml: 36.7 vs. 4.3, respectively, p = 0.001) and correlated inversely with CD4+ T cell counts (q = - 0.65; p = 0.005). Patients receiving ART and TMP-SMX had a significant reduction in LBP between BL and 1 year (median, lg/ml: 36.7 vs. 11.1; p = 0.003). In contrast, levels of LPS at BL were lower in patients starting ART and TMP-SMX compared to those without TMP-SMX (median, pg/ml: 221 vs. 303 respectively; p = 0.002) and did not change at 1 year. The increased BL levels of sCD14 had declined in both groups at 1 year. No difference in I-FABP levels was found between BL and 1 year. Concomitant use of ART and TMP-SMX reduces microbial translocation markers LBP and sCD14, probably due to its impact on the gut microbiota. Effective ART for 1 year does not restore gut–blood barrier dysfunction.

Introduction

T

he lymphoid tissue in the gut is infected by human immunodeficiency virus type 1 (HIV-1) very early after infection,1,2 resulting in damage to the gut–blood barrier. This includes a permanent loss of Th17+ CD4+ T cells, impaired antimicrobial mucosal immunity, changes in enterocyte homeostasis,3 and translocation of microbial products to the blood. Although antiretroviral therapy (ART) leads to a pronounced inhibition of the viral replication and recovery of CD4+ T cells, this translocation persists.4 The level of microbial translocation (MT) is similar to the levels in diseases such as inflammatory bowel diseases, coeliac disease, and sepsis, and its role in chronic immune activation and inflammation in HIV-1 infection has been detailed.5–7 MT can be studied using several direct markers in blood such as lipopolysaccharide (LPS) and bacterial 16S rDNA.8–11 In addition, indirect markers are used such as soluble CD14 (sCD14), a protein secreted from monocytes activated by bacterial or viral stimuli, lipopolysaccharide-binding protein

(LBP), an acute-phase protein synthetized mainly in the liver upon LPS stimuli, interleukin (IL)-6, D-dimer, and antiflagellin antibodies.12–16 Additionally, intestinal fatty acid binding protein (I-FABP), a protein released from enterocytes undergoing cell death, is used as a marker of gut permeability.17 Antibiotics influence the composition of the gut microbiota. Hence, Helicobacter pylori eradication with metronidazole and clarithromycin for 7 days in patients with dyspeptic disorders had both short-term and long-term effects on the intestinal microbiota.18 In addition, treatment with oral vancomycin for 1 week reduced fecal microbial diversity, causing a population shift from gram-positive to gramnegative bacteria.19 Thus, use of antibiotics might change the commensal gut microbiota and reduce the total bacterial load, which may impact the magnitude of MT. The link between antibiotic use and MT has emerged in several studies. For example, rifaximin, a nonabsorbable broad-spectrum oral antibiotic, was shown to reduce MT in patients with decompensated cirrhosis.20 In a model with

1

Department of Medicine, Unit of Infectious Diseases, Karolinska Institutet, Karolinska University Hospital Huddinge, Stockholm, Sweden. Department of Laboratory Medicine, Division of Clinical Microbiology, Karolinska Institutet, Karolinska University Hospital Huddinge, Stockholm, Sweden. 3 Department of Infectious Diseases, County Council of Ga¨vleborg, Ga¨vle, Sweden. 2

830

TMP-SMX EFFECT ON MICROBIAL TRANSLOCATION

simian immunodeficiency virus-infected monkeys, 2 weeks of treatment with neomycin, metronidazole, and cefotaxime led to a significant decrease in MT.4 However, although several studies have reported an increased MT in HIV-1infected patients,4,8,21 only a few have reported the impact of antibiotics.10,16 In our previous work, levels of sCD14 were affected by antibiotic use in HIV-1 patients starting ART.10 In addition, we have shown that the use of tuberculostatics decreases MT.16 Based upon these observations, we hypothesized that the levels of MT markers may be influenced by the use of cotrimoxazole (TMP-SMX) in patients who receive it as prophylaxis against Pneumocystis jiroveci. Such knowledge can be valuable for the interpretation of studies of MT in HIV-1infected patients with advanced disease. We therefore analyzed several biomarkers for MT in plasma obtained at baseline, at 1 month follow-up, and at 1 year in treatmentnaive patients with immunodeficiency who received TMPSMX as prophylaxis together with first line ART. Materials and Methods Subjects

Patients with HIV-1 infection (n = 26) followed at the Department of Infectious Diseases, Karolinska University Hospital, Stockholm, Sweden, who initiated first line ART, were selected from a larger cohort based on sample availability (Table 1). They were divided into two groups depending on whether they started ART and concomitantly TMP-SMX prophylaxis against Pneumocystis jiroveci (160 mg/800 mg three times a week) (n = 13) or not (n = 13). TMP-SMX was started at a median of 7 days (IQR 1.5–21) and ART 12 days (7.5–15) after the first visit (baseline; BL) at the clinic. In the non-TMP-SMX group ART was initiated 21 days (8.5–52) after BL. ART consisted of two nucleoside reverse transcriptase inhibitors (NRTIs): tenofovir (n = 15)

831

and abacavir (n = 6) or zidovudine (n = 4) in combination with lamivudine/emtricitabine, and the nonnucleoside reverse transcriptase inhibitor (NNRTI) efavirenz (n = 7) or one of the ritonavir-boosted protease inhibitors (PI/r) lopinavir (n = 8), darunavir (n = 4), or atazanavir (n = 6), with the exception of one patient in the group of ART who was treated only with the integrase inhibitor raltegravir + darunavir/r. Plasma samples had been drawn as a part of clinical care and kept at -70C until analysis. Three samples of each patient were analyzed at BL, 1 month (follow-up 1; FU1), and 1 year (FU2). The time between BL and FU1 was a median of 38 days (IQR 31–56) in the TMP-SMX group and 58 days (40–70) in the non-TMP-SMX group. TMP-SMX was given for a median of 27 days (25–50) before FU1. The time between BL and FU2 was a median of 51 weeks (IQR 44–52) and 46 weeks (41–57), respectively. Five of the 13 patients continued the prophylaxis until FU2. The other eight were on TMP-SMX for a median of 176 days (IQR 58–208). Three patients had AIDS events (extrapulmonary tuberculosis, candida esophagitis, Kaposi’s sarcoma) at the time of HIV diagnosis in the TMP-SMX group, but none in the other group. The study was approved by the Regional Ethics Committee at the Karolinska Institutet (Dnr 2009/1485-31). CD4+ T cells and plasma HIV-1 RNA

Analysis of CD4+ T cell counts and plasma HIV RNA load was performed as part of the clinical routine with flow cytometry and COBAS Taqman HIV-1 RNA test v.2.0 (Roche Molecular Systems Inc., Branchburg, NJ), respectively. Quantification of microbial translocation markers

LPS levels were determined by the Limulus Amebocyte Lysate Assay (LAL, Lonza, MD) according to the manufacturer’s instructions, with the following modifications: samples were diluted 5-fold to avoid interference with

Table 1. Characteristics of the HIV-1-Infected Patient-Cohorts at Start of Antiretroviral Therapy Together With or Without Concomitant Co-trimoxazole (TMP-SMX) Treatment All

TMP-SMX group

Non-TMP-SMX group

Subjects, number 26 13 13 Age, years: median (range) 39 (25–70) 42 (25–70) 37 (25–70) Sex (male/female) 16/10 8/5 8/5 Hepatitis, number B/Ca 1/3 1/2 0/1 CD4+ T cells/ll: median (range) 180 (0–350) 100 (0–190)b 260 (110–350) HIV-1 RNA copies/ml: 153,000 (3,690–10,000,000) 276,000 (26,500–10,000,000) 99,700 (3,690–48,300) median (range) Mode of transmission Heterosexual 14 7 7 MSM 6 3 3 PWID 3 2 1 Blood transfusion 1 0 1 Unknown 2 1 1 Use of tenofovir, number 15 10 5 Days to follow-up 1: median (IQR) 47 (36–62) 38 (31–56) 58 (40–70) Weeks to follow-up 2: 50 (44–56) 51 (44–52) 46 (41–57) median (IQR) a

One (in TMP-SMX group, with hepatitis C) of four patients with hepatitis had cirrhosis. The baseline CD4+ T cell count was significantly lower in the co-trimoxazole (TMP-SMX) group ( p < 0.0001). MSM, men who have sex with men; PWID, people with intravenous drug use.

b

832

background color and preheated to 70C for 12 min prior to analyses to dissolve immune complexes, as described elsewhere.8 Linear regression analysis was performed to obtain the corresponding endotoxin concentration of the samples from their absorbance values (background was subtracted after each run). Quantifications of LBP, sCD14, and I-FABP levels were performed by enzyme-linked immunosorbent assays (Hycult biotech, the Netherlands; R&D Systems, USA; DS Pharma Biomedical Co., Japan, respectively) according to the manufacturer’s instructions. Statistical analysis

Comparisons between independent groups were performed by the Mann–Whitney U test. Longitudinal analyses were performed by the Wilcoxon matched pairs test. The relationship between two variables was determined with Spearman’s correlation. Changes in LPS, LBP, sCD14, and I-FABP from BL to FU1 and FU2 were analyzed with a generalized linear mixed-effects model adjusted by gender, age, viral load, and CD4+ T cells at BL. The model included a

VESTERBACKA ET AL.

random intercept and random slope that allowed individual variations in the change of the MT markers over time. Data were analyzed by GraphPad Prism 5.04 and STATA 12 SE/ 12 and presented as median and as IQR if not stated otherwise. A p-value < 0.05 was considered significant. Results CD4+ T cells and HIV-1 RNA

At BL, the median CD4+ T cell count was 100 cells/ll (IQR 50–145) and 260 cells/ll (205–325), respectively, in the patients who thereafter received prophylaxis or not ( p < 0.0001) (Table 1). The T cell recovery from BL to FU2 did not differ significantly between the groups. No significant difference in HIV-1 load was found between the groups at BL (median, copies/ml: 276,000 vs. 99,700) ( p = 0.087). At FU1, the viral load was higher in the TMP-SMX group (1,740 vs. 800 copies/ml; p = 0.027). At FU2, no difference was found in the proportion of patients with >50 copies/ml [in the TMPSMX group 4/12 (of whom there were two blips) and in the non-TMP-SMX group 2/13 (both blips)]. Blips were defined

FIG. 1. Baseline (BL) levels of lipopolysaccharide (LPS) were lower in the co-trimoxazole group (TMP-SMX) compared to the non-co-trimoxazole group (non-TMP-SMX) ( p = 0.002) and did not change significantly in any of the groups between BL and follow-up 2 (FU2) (A). Lipopolysaccharide-binding protein (LBP) levels at BL were elevated in the TMP-SMX group compared to the non-TMP-SMX group ( p = 0.001) and were significantly reduced at FU2 in TMP-SMX only ( p = 0.003) (B). CD4+ T cells and LBP were significantly negatively correlated at BL (C). BL levels of sCD14 tended to be higher in TMP-SMX ( p = 0.07), and decreased longitudinally until FU2 in both groups (TMP-SMX; p = 0.001, non-TMP-SMX; p = 0.02) (D). Horizontal bars indicate median values. Comparisons between independent groups were performed using the Mann–Whitney U test, and the Wilcoxon matched pairs test was used for longitudinal analyses. Spearman’s rank test was applied for correlations. *p < 0.05, **p < 0.01, ***p < 0.001.

TMP-SMX EFFECT ON MICROBIAL TRANSLOCATION

as intermittent periods of detectable low-level viremia that return spontaneously to an undetectable level without any change in ART. Lack of change in LPS levels during 1 year of ART

833

Table 2. Adjusted Analysis of Mean Change of LBP (A) and sCD14 (B) During Antiretroviral Therapy, With or Without Concomitant Co-Trimoxazole (TMP-SMX) Treatment A. LBP

Coefficient (95% CI)a

p-value

+

CD4 T cells and LPS correlated positively at BL (q = 0.46; p = 0.02). The LPS levels were lower in the TMP-SMX group compared to the non-TMP-SMX group (pg/ml: 221; 159–266 vs. 302; 289–346; p = 0.002), despite higher CD4+ T cells in the latter group. The difference persisted at FU1 and FU2 ( p = 0.003 vs. 0.004, respectively) (Fig. 1A). LPS levels increased significantly between BL and FU1 in the non-TMPSMX group only (pg/ml: 302; 289–346 vs. 329; 313–354; p = 0.0007). There was no significant change in LPS levels between BL and FU2 within the two groups, and the same result was revealed by the generalized linear mixed-effects model. When stratifying the patients into two groups based upon LPS increase or decrease between BL and FU2, individuals with declining LPS (n = 7) tended to have a better CD4+ T cell recovery (cells/ll: 340; 200–400 vs. 150; 110–215; p = 0.057).

Non TMP-SMX FU FU2 TMP-SMX FU FU2 B. sCD14

- 2.9 (-11.8–6.1) 1.2 (-7.3–9.7) - 0.6 (-13.3–12.1) - 24.4 (-36.5– -12.4) Coefficient (95% CI)a

Non TMP-SMX FU - 147067.7 FU2 - 1271497 TMP-SMX FU - 56090.7 FU2 - 217981

0.53 0.79 0.93 < 0.001 p-value

(-807317.9–513182.5) (-2039733– - 503260.7)

0.662 0.001

(-989825.5–877644.1) (-1304168–868205.6)

0.906 0.694

a

Decrease of LBP levels after 1 year in TMP-SMX-treated patients

At BL, LBP levels were elevated in the TMP-SMX group compared to the non-TMP-SMX group (lg/ml: 36.7; 14.1– 49.9 vs. 4.3; 2.2–14.5; p = 0.001) (Fig. 1B). The levels remained elevated in the TMP-SMX group at FU1. No differences between the groups were found at FU2. In the TMPSMX group, a reduction in the LBP level was seen between BL and FU2 (11.1; 4.5–18.7) ( p = 0.003), but not in the other group (8.9; 5.9–14.5) ( p = 0.47) (Fig. 1B). The different kinetics of LBP between the groups persisted in the generalized linear mixed-effects model, where patients who did not receive TMP-SMX prophylaxis had a nonsignificant increase in LBP at FU2, as opposed to patients with prophylaxis who had a decrease (Table 2A). At BL, a negative correlation between CD4+ T cells and LBP was seen (q = - 0.65; p = 0.005) (Fig. 1C) and a positive correlation was seen between LBP and sCD14 (q = 0.42; p = 0.03), but not at FU1 and FU2. LPS and LBP were negatively correlated at BL (q = - 0.45; p = 0.03) and FU2 (q = - 0.65; p = 0.002). Levels of sCD14 were reduced by ART

At BL, VL and sCD14 were positively correlated (q = 0.55; p = 0.005) and the levels of sCD14 tended to be higher in the TMP-SMX group (lg/ml: 3.7 · 106; 3.1–4.3 · 106 vs. 2.9 · 106; 1.8–3.9 · 106; p = 0.07). A significant reduction was seen between BL and FU2 in both groups ( p = 0.001; p = 0.02, respectively) (Fig. 1D). After adjustment for covariables in the generalized linear mixed-effects model, sCD14 levels decreased significantly between BL and FU2 in the non-TMP-SMX group only (Table 2B). Elevated levels of I-FABP associated with use of tenofovir

At BL, the groups had similar levels of I-FABP (Fig. 2A). In the TMP-SMX group, the levels increased from BL to FU1 (1.68; 0.99–2.7 vs. 4.67; 1.49–8.19) ( p = 0.001) and a decrease was seen at FU2, to levels similar to those at BL. In the non-TMP-SMX group, I-FABP levels at FU1 and FU2 were

Generalized linear mixed-effects model with a random intercept and random slope adjusted by gender, age, viral load, and CD4 at baseline. FU, first time point of follow-up; FU2, second time point of follow-up. Non TMP-SMX refers to patients who did not receive prophylaxis and TMP-SMX to those who received prophylaxis. LBP, lipopoly saccharide-binding protein; sCD14, soluble CD14.

similar to BL levels. No significant differences in the kinetics of I-FABP were revealed in the generalized linear mixedeffects model. After stratifying the patients into groups based upon IFABP increase or decrease between BL and FU1, the CD4+ T cell recovery was found to be 103 cells/ll in the group with increasing I-FABP levels and 210 cells/ll in the group with decreasing I-FABP levels, respectively ( p = 0.02). Patients were also categorized according to chosen NRTI-based ART. In the group (n = 15) with tenofovir-based ART, I-FABP levels increased from BL (ng/ml 1.92; 1.26–3.15) to FU1 (4.13; 2.62–6.44; p = 0.0003) (Fig. 2B). At FU2, the levels had declined to levels similar to the BL (data not shown). However, patients with non-tenofovir-based ART (n = 11) did not have significantly altered I-FABP levels. Discussion

It is well established that MT is increased in immunodeficient HIV-1-infected patients, although there are diverging results regarding the extent of the MT and how it is influenced by ART.4,9,21 Also, metagenomics data show that the gut microbiota is changed in HIV-1-infected individuals.22,23 One possible confounding factor is the use of antibiotics/antifungals since the effects of these drugs on the microbiome are significant and can persist for a long time.18,20,24 We hypothesized that the influence of such a drug may also be reflected in the markers of systemic inflammation and MT. Therefore, the kinetics of MT markers was assessed in treatment-naive patients starting ART with or without TMP-SMX. Our findings at baseline clearly confirmed that MT is present in untreated patients with immunodeficiency. Thus, levels of well-established MT markers (LPS, LBP, sCD14, and I-FABP) were increased compared to historical healthy controls and the CD4+ T cells correlated negatively with

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FIG. 2. Similar levels of intestinal fatty acid binding protein (I-FABP) were observed in the co-trimoxazole (TMP-SMX) group and the non-co-trimoxazole (non-TMP-SMX) group at baseline (BL), and increased between BL and follow-up (FU) in the TMP-SMX group ( p = 0.001), but did not change significantly between BL and follow-up 2 (FU2) in any group (A). Tenofovir (TDF)-treated patients had a significant elevation of I-FABP at FU compared to BL ( p = 0.0003) (B). Horizontal bars indicate median values. Comparisons between independent groups were performed using the Mann–Whitney U test, and the Wilcoxon matched pairs test was used for longitudinal analyses. **p < 0.01, ***p < 0.001. LBP.25 However, we report a positive correlation between LPS levels and the CD4+ T cells, in contrast to our findings in a previous work.10 A similar finding was reported by Marchetti et al. with low LPS levels in severely immune compromised patients.26 A possible explanation is a compositional shift of patients microbiome in the severely immune compromised subjects23 studied here and/or the impact of a more frequent use of antibiotics in such patients. Thus, in our study five out of 13 patients in the TMP-SMX group received antibiotics and/or antifungals within 3 months, and an additional three patients 6 months before the baseline visit, compared to only one patient in the ART group. These antibiotic-treated patients tended to have lower LPS levels at BL, but the difference did not reach statistical significance (data not shown). Thus, a consequent change in the composition of the gut microbiota with a relative decrease in gram-negative species could have resulted in the lower LPS levels. Other alternative explanations could be an increased LPS clearance, mirrored by a negative correlation between LPS and LBP, or intestinal bacterial overgrowth with a gram-positive microbiota shift.4 It is clearly unlikely that 1 month of ART will improve the damage to the gut–blood barrier and any changes in MT biomarkers at that time point represent other biological events. In our study, the I-FABP levels increased after 1 month among the patients who received ART and TMPSMX. Tenofovir use was more prevalent in this group, and tenofovir-treated individuals had significantly higher levels of I-FABP at 1 month. We speculate that the transient enterocyte damage (reflected by higher I-FABP levels) might be linked to temporary enterocyte toxicity, as higher tenofovir concentrations have been observed in the gut compartment compared to the blood.27 Still, an immune reconstitution syndrome (IRIS) in the gut cannot be dismissed. The latter hypothesis is supported by the finding of increased LPS levels at month 1 in the ART-treated group since an IRIS in the gut is likely to increase the permeability for bacterial products. However, in a recent large cohort study on HIV-TB-coinfected patients receiving TB treatment and starting ART, levels of

I-FABP after 1 month of ART were lower, but LBP levels were higher in patients when compared to patients without IRIS.28 Intestinal biopsies are needed to determine if IRIS in the gut compartment influences I-FABP levels. Conflicting results of LPS kinetics during ART have been reported with both decreasing and unaltered levels.4,8,9,29 We have previously reported that MT decreases, but still persists, after 72 weeks of successful ART.10 The present study included a shorter follow-up (median 51 weeks), but the patients had a more advanced immunodeficiency at baseline than in our earlier study. In line with our earlier results, a reduction in the sCD14 levels was observed at 1 year in both treatment groups.10,16,29 In addition, the LPS levels did not decline or normalize during this short follow-up. Overall, LPS levels have declined between BL and FU2 in only seven patients (four in the TMP-SMX group), who tended to have a more favorable CD4 T cell recovery. It is difficult to reach a solid conclusion concerning this relationship because of the small cohort size, but the higher CD4 T cell reconstitution in blood may reflect decreased bacterial translocation across the gut–blood barrier due to local reconstitution in gutassociated lymphoid tissue. In contrast, the LBP levels declined in the patients who received TMP-SMX. LPB can be induced and bind other bacterial products (such as peptidoglycans) from, e.g., gram-positive bacteria. Thus, these broad microbiological triggers of LBP will be reduced by TMP-SMX use, as the total bacterial load in the gut decreases, contributing to the reduction in LBP in the group of antibiotic-treated patients only. The discrepancy in LBP kinetics between the groups persisted even when adjusting for CD4+ T cell count in the generalized linear mixed-effects model. This suggests that the reduction in LBP in the TMP-SMX group was related to the antibiotic prophylaxis, and not to different levels of baseline immunodeficiency between the groups. The strength of our study is the longitudinal design; to date there have been relatively few studies assessing the long-term kinetics of MT markers during HIV-1 infection.10,16,29–31 Additionally, none has analyzed the impact of the use of antibiotics on this process except for our earlier studies in

TMP-SMX EFFECT ON MICROBIAL TRANSLOCATION

which data indicate that antibiotics may influence the levels of MT biomarkers.10,16This issue was highlighted in a recent review of co-trimoxazole prophylaxis during HIV infection.32 Our study has obvious limitations. We retrospectively analyzed a small cohort of patients, which limits the opportunities to detect more subtle differences between groups. The groups had differences in CD4+ T cell counts at the start, but those did not influence the results when the model adjusting for significant covariables was applied. As it was a retrospective study, we could not avoid the differences in timing of specimen collection, which might have influenced the differences between groups at FU1. Furthermore, characterization of the gut microbiome was not performed, restricting the possibility of correlating our findings with antibiotic-related alternations of the gut flora. In summary, our results indicate that use of TMP-SMX is likely to affect LBP, which is an important biomarker of MT. This should be considered when studies on the effects of ART on MT in HIV-1-infected patients are analyzed. Additionally, an I-FABP elevation was detected after 1 month of ART, with a possible link to tenofovir. Our pilot study warrants largescaled studies to further clarify whether HIV-1 drugs affect the level of enterocyte cell death and the influence of antibiotics on MT in HIV-1-infected patients. Acknowledgments

We thank Professor Anders So¨nnerborg for valuable comments. The study was supported by Stockholm’s County Council (SLL-KI), Swedish Physician Against AIDS Research Fund, County Council of Ga¨vleborg, and Swedish Society for Medical Research (SSMF for Piotr Nowak). Parts of the data were presented at a poster session during the HIV Nordic Conference, October 2–3, 2014, Stockholm, Sweden. Author Disclosure Statement

No competing financial interests exist. References

1. Guadalupe M, Reay E, Sankaran S, et al.: Severe CD4+ Tcell depletion in gut lymphoid tissue during primary human immunodeficiency virus type 1 infection and substantial delay in restoration following highly active antiretroviral therapy. J Virol 2003;77(21):11708–11717. 2. Kotler DP, Reka S, Borcich A, and Cronin WJ: Detection, localization, and quantitation of HIV-associated antigens in intestinal biopsies from patients with HIV. Am J Pathol 1991;139(4):823–830. 3. Brenchley JM, Paiardini M, Knox KS, et al.: Differential Th17 CD4 T-cell depletion in pathogenic and nonpathogenic lentiviral infections. Blood 2008;112(7):2826–2835. 4. Brenchley JM, Price DA, Schacker TW, et al.: Microbial translocation is a cause of systemic immune activation in chronic HIV infection. Nat Med 2006;12(12):1365–1371. 5. Lakatos PL, Kiss LS, Palatka K, et al.: Serum lipopolysaccharide-binding protein and soluble CD14 are markers of disease activity in patients with Crohn’s disease. Inflamm Bowel Dis 2011;17(3):767–777. 6. Assimakopoulos SF, Papageorgiou I, and Charonis A: Enterocytes’ tight junctions: From molecules to diseases. World J Gastrointest Pathophysiol 2011;2(6):123–137.

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7. Opal SM, Scannon PJ, Vincent JL, et al.: Relationship between plasma levels of lipopolysaccharide (LPS) and LPS-binding protein in patients with severe sepsis and septic shock. J Infect Dis 1999;180(5):1584–1589. 8. Troseid M, Nowak P, Nystrom J, et al.: Elevated plasma levels of lipopolysaccharide and high mobility group box-1 protein are associated with high viral load in HIV-1 infection: Reduction by 2-year antiretroviral therapy. AIDS 2010;24(11):1733–1737. 9. Merlini E, Bai F, Bellistri GM, et al.: Evidence for polymicrobic flora translocating in peripheral blood of HIV-infected patients with poor immune response to antiretroviral therapy. PLoS One 2011;6(4):e18580. 10. Vesterbacka J, Nowak P, Barqasho B, et al.: Kinetics of microbial translocation markers in patients on efavirenz or lopinavir/r based antiretroviral therapy. PLoS One 2013; 8(1):e55038. 11. Svard J, Sonnerborg A, Vondracek M, et al.: On the usefulness of circulating bacterial 16S rDNA as a marker of microbial translocation in HIV-1-infected patients. J Acquir Immune Defic Syndr 2014;66(4):e87–89. 12. Nowak P, Abdurahman S, Lindkvist A, et al.: Impact of HMGB1/TLR ligand complexes on HIV-1 replication: Possible role for flagellin during HIV-1 infection. Int J Microbiol 2012;2012:263836. 13. Sandler NG and Douek DC: Microbial translocation in HIV infection: Causes, consequences and treatment opportunities. Nat Rev Microbiol 2012;10(9):655–666. 14. Lichtfuss GF, Hoy J, Rajasuriar R, et al.: Biomarkers of immune dysfunction following combination antiretroviral therapy for HIV infection. Biomark Med 2011;5(2):171– 186. 15. Grube BJ, Cochane CG, Ye RD, et al.: Lipopolysaccharide binding protein expression in primary human hepatocytes and HepG2 hepatoma cells. J Biol Chem 1994;269(11): 8477–8482. 16. Abdurahman S, Barqasho B, Nowak P, et al.: Pattern of microbial translocation in patients living with HIV-1 from Vietnam, Ethiopia and Sweden. J Int AIDS Soc 2014; 17:18841. 17. Pelsers MM, Hermens WT, and Glatz JF: Fatty acidbinding proteins as plasma markers of tissue injury. Clin Chim Acta 2005;352(1–2):15–35. 18. Jakobsson HE, Jernberg C, Andersson AF, et al.: Shortterm antibiotic treatment has differing long-term impacts on the human throat and gut microbiome. PLoS One 2010; 5(3):e9836. 19. Vrieze A, Out C, Fuentes S, et al.: Impact of oral vancomycin on gut microbiota, bile acid metabolism, and insulin sensitivity. J Hepatol 2014;60:824–831. 20. Kalambokis GN and Tsianos EV: Rifaximin reduces endotoxemia and improves liver function and disease severity in patients with decompensated cirrhosis. Hepatology 2012;55(2):655–656. 21. Cassol E, Malfeld S, Mahasha P, et al.: Persistent microbial translocation and immune activation in HIV-1-infected South Africans receiving combination antiretroviral therapy. J Infect Dis 2010;202(5):723–733. 22. Vujkovic-Cvijin I, Dunham RM, Iwai S, et al.: Dysbiosis of the gut microbiota is associated with HIV disease progression and tryptophan catabolism. Sci Transl Med 2013;5(193):193ra191. 23. Nowak P BB, Avershina E, Noyan K, et al.: Decreased Diversity of Gut Microbiota Is Associated with Immune Status

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during HIV-1 Infection. Abstract Conference on Retroviruses and Opportunistic Infections (CROI) 2014. 2014. Dethlefsen L and Relman DA: Incomplete recovery and individualized responses of the human distal gut microbiota to repeated antibiotic perturbation. Proc Natl Acad Sci USA 2011;108(Suppl 1):4554–4561. Ipp H, Zemlin AE, Glashoff RH, et al.: Serum adenosine deaminase and total immunoglobulin G correlate with markers of immune activation and inversely with CD4 counts in asymptomatic, treatment-naive HIV infection. J Clin Immunol 2013;33(3):605–612. Marchetti G, Merlini E, Sinigaglia E, et al.: Immune reconstitution in HIV+ subjects on lopinavir/ritonavir-based HAART according to the severity of pre-therapy CD4 + . Curr HIV Res 2012;10(7):597–605. Di Mascio M, Srinivasula S, Bhattacharjee A, et al.: Antiretroviral tissue kinetics: In vivo imaging using positron emission tomography. Antimicrob Agents Chemother 2009;53(10):4086–4095. Goovaerts O, Jennes W, Massinga-Loembe M, et al.: LPSbinding protein and IL-6 mark paradoxical tuberculosis immune reconstitution inflammatory syndrome in HIV patients. PLoS One 2013;8(11):e81856. Wallet MA, Rodriguez CA, Yin L, et al.: Microbial translocation induces persistent macrophage activation un-

related to HIV-1 levels or T-cell activation following therapy. AIDS 2010;24(9):1281–1290. 30. Chevalier MF, Petitjean G, Dunyach-Remy C, et al.: The Th17/Treg ratio, IL-1RA and sCD14 levels in primary HIV infection predict the T-cell activation set point in the absence of systemic microbial translocation. PLoS Pathog 2013;9(6):e1003453. 31. Pallikkuth S, Fischl MA, and Pahwa S: Combination antiretroviral therapy with raltegravir leads to rapid immunologic reconstitution in treatment-naive patients with chronic HIV infection. J Infect Dis 2013;208(10):1613–1623. 32. Church JA, Fitzgerald F, Walker AS, et al.: The expanding role of co-trimoxazole in developing countries. Lancet Infect Dis 2015;15(3):327–339.

Address correspondence to: Jan Vesterbacka Department of Medicine Unit of Infectious Diseases I73 Karolinska Institutet Karolinska University Hospital Huddinge SE-141 86 Stockholm Sweden E-mail: [email protected]

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Gut microbiota diversity predicts immune status in HIV-1 infection Piotr Nowaka,M, Marius Troseidb,c,M, Ekatarina Avershinad, Babilonia Barqashoe, Ujjwal Neogie, Kristian Holmc,f,g, Johannes R. Hovc,f,g, Kajsa Noyane, Jan Vesterbackaa, Jenny Sva¨rde, Knut Rudid and Anders So¨nnerborga,e Objective: HIV-1 infection is characterized by altered intestinal barrier, gut microbiota dysbiosis, and systemic inflammation. We hypothesized that changes of the gut microbiota predict immune dysfunction and HIV-1 progression, and that antiretroviral therapy (ART) partially restores the microbiota composition. Design: An observational study including 28 viremic patients, 3 elite controllers, and 9 uninfected controls. Blood and stool samples were collected at baseline and for 19 individuals at follow-up (median 10 months) during ART. Methods: Microbiota composition was determined by 16S rRNA sequencing (Illumina MiSeq). Soluble markers of microbial translocation and monocyte activation were analyzed by Limulus Amebocyte Lysate assay or ELISA. Results: Several alpha-diversity measures, including number of observed bacterial species and Shannon index, were significantly lower in viremic patients compared to controls. The alpha diversity correlated with CD4þ T-cell counts and inversely with markers of microbial translocation and monocyte activation. In multivariate linear regression, for every age and sex-adjusted increase in the number of bacterial species, the CD4þ T-cell count increased with 0.88 (95% confidence interval 0.35–1.41) cells/ ml (P ¼ 0.002). After introduction of ART, microbiota alterations persisted with further reduction in alpha diversity. The microbiota composition at the genus level was profoundly altered in viremic patients, both at baseline and after ART, with Prevotella reduced during ART (P < 0.007). Conclusions: Gut microbiota alterations are closely associated with immune dysfunction in HIV-1 patients, and these changes persist during short-term ART. Our data implicate that re-shaping the microbiota may be an adjuvant therapy in patients commencing successful ART. Copyright ß 2015 Wolters Kluwer Health, Inc. All rights reserved.

AIDS 2015, 29:000–000 Keywords: elite controllers, microbial translocation, microbiota, Shannon alpha-diversity index

a Department of Medicine Huddinge, Unit of Infectious Diseases, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden, bDepartment of Infectious Diseases, Oslo University Hospital, Ulleva˚l Hospital, cK.G. Jebsen Centre for Inflammation ˚ s, Norway, eDepartment of Laboratory Medicine, Research, University of Oslo, Oslo, dNorwegian University of Life Sciences, A Division of Clinical Microbiology, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden, fNorwegian PSC Research Centre, Dept of Transplantation Medicine and Section of Gastroenterology, and gResearch Institute of Internal Medicine, Division of Cancer Medicine, Surgery and Transplantation, Oslo University Hospital, Oslo, Norway. Correspondence to Piotr Nowak, Department of Medicine Huddinge, Unit of Infectious Diseases, I73, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden. Tel: +46 858580000; fax: +46 858587933; e-mail: [email protected]  The authors contributed equally to this work. Received: 29 April 2015; revised: 17 August 2015; accepted: 27 August 2015.

DOI:10.1097/QAD.0000000000000869

ISSN 0269-9370 Copyright Q 2015 Wolters Kluwer Health, Inc. All rights reserved.

Copyright © 2015 Wolters Kluwer Health, Inc. Unauthorized reproduction of this article is prohibited.

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Introduction The gut-associated lymphoid tissue (GALT) is an essential part of the immunological network that maintains integrity of the gastrointestinal tract against microbes in the gut lumen, denoted as the gut microbiota [1]. HIV type 1 (HIV-1) infection starts with a massive destruction of CD4þ T cells residing in the GALT, leading to structural and functional changes in the mucosal immunity [2,3]. Thus, CD4þ T cells, especially T-helper 17 (Th17) cells, which have a crucial role in maintaining the gut immunological barrier, are depleted early during HIV-1 infection [4]. The depletion of Th17 T cells creates a pathogenic milieu where the supervision of microbial species is less effective, leading to increased permeability of the gut– blood barrier [5]. Hence, parts of the bacteria enter the systemic circulation in a process termed as microbial translocation, contributing to inflammation, immune activation, and ultimately exhaustion of the immune system [6,7]. Additionally, the alterations in the mucosal immune system could affect the gut microbiota composition [8,9]. Thus, changes in the gut microbiota during chronic HIV-1 infection are likely to contribute to low-grade inflammation in the gut and consequently also in the circulation, thereby fueling and maintaining the HIV-associated immune dysfunction [10]. Antiretroviral therapy (ART) appears to at least partially restore the gut integrity, although microbial translocation and inflammation are not reduced to the levels seen in uninfected persons [11–13]. Also, the impact of ART on the gut microbiota is not well described. In the past year, cross-sectional studies have demonstrated changed gut microbiota in HIV-1-infected patients, but there are no published longitudinal studies reporting the effect of ART on microbiota composition (reviewed in [14]). We hypothesized that alterations of the gut

microbiota would predict immune dysfunction and HIV-1 progression, and that introduction of ART would partially restore the gut microbiota composition.

Methods Study participants An observational cohort of 31 HIV-1-infected individuals was recruited from the HIV Outpatient Clinic at Karolinska University Hospital, Stockholm, Sweden (Table 1 and Supplementary Table ST1, http:// links.lww.com/QAD/A770). Additionally, a sex and age-matched control group of nine healthy HIV-1seronegative individuals (CTR) was included, consisting of household members and partners of the patients, to avoid major differences in food intake, ethnicity, and social background. Stool and peripheral blood samples were collected from all study participants at baseline and for 19 patients at follow-up (median 10 months; interquartile range 4–15) after ART introduction. ART consisted of two nucleoside reverse transcriptase inhibitors (NRTIs) in combination with a non-nucleoside reverse transcriptase inhibitor (NNRTI; n ¼ 8) or a ritonavir-boosted protease inhibitor (n ¼ 11). Neither patients nor controls had been prescribed antibiotics or consumed probiotics during the preceding 2 months, or had infectious diarrhea. The Regional Ethical Committee (Stockholm, Sweden, Dnr 2009-1485-31-3) had approved the study. All participants provided written informed consent in accordance with the Declaration of Helsinki. T-cell populations and viral load Analyses of CD4þ and CD8þ T-cell counts and plasma HIV-1 RNA load were performed as part of the clinical routine with flow cytometry and Cobas Amplicor (Roche Molecular Systems Inc., Branchburg, New Jersey, USA), respectively.

Table 1. Cohort characteristics at baseline.

Number of participants Age (years) Sex (male/female) Ethnicity: Caucasian/African/Oriental Mode of transmission: MSM/IVDU/HS Years since diagnosis CD4þ T-cell count (cells/ml) CD4þ T-cell % CD8þ T-cell count (cells/ml) CD8þ T-cell % HIV RNA (copies/ml) CD4þ/CD8þ ratio BMI

HIV-1-infected patients

Healthy controls

31 40.5 (19–67) 16/15 16/13/2 7/6/18 3 (1–26) 355 (120–2470) 18 (5–60) 970 (380–2390) 56.5 (23–88) 48800 (20 copies/ml) at baseline and are further referred to as viremic patients. The remaining three participants were classified as elite controllers [undetectable HIV-1 RNA since diagnosis of HIV-1 infection (median 20 years)]. Six patients (among viremic patients) had a highly deteriorated immune status at baseline (median CD4þ T-cell count 135 cells/ml; range 120–150) and they are referred to as immune defect patients. Fifteen of the 19 patients who received ART had undetectable viral load at follow-up, and the remaining 4 had low levels (median 60 copies/ml; range 29–224). Median CD4þ T-cell recovery for the whole treated group at follow-up was 140 cells/ml (range 0–740). The analyzed dataset contained sequences from 31 patients and 9 control individuals at baseline. Sixteen (of 19) patients who initiated ART had follow-up data (10 000 sequences per sample). Decreased alpha diversity in untreated HIV-1infected patients At baseline, the number of observed bacterial species was lower in the HIV-1-infected patients as compared to the controls, independent of the number of bacterial sequences analyzed per sample (Fig. 1a) and independent of whether the three elite controllers were included or not. The lowest number of bacterial species was present among the patients with the lowest CD4þ T-cell counts (immune defect patients) (Fig. 1b).

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0

2000

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9) = TR C

ID

(n

(n

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(n

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EC

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p = 0.03 500

=

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)

Number of observed bacterial species

(b) Number pf observed bacterial species

(a)

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AIDS

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(d) p = 0.01

CD4 + T cell cont (cells/µl)

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7 6 5 4

Controls (n = 9)

300 200 100 0

HIV-1 (n = 31)

0 0

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di h ig H

Lo w

di

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ve r

ve r

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ty

ty

(n

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(n

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)

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)

8

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Sequences per sample

Fig. 1. Differences of alpha diversity indexes in untreated HIV-1-infected patients as compared to controls at baseline. (a) Number of observed bacterial species in relation to number of analyzed sequences. (b) Distribution of number of observed bacterial species. (c) Shannon alpha-diversity index. (d) The distribution of CD4þ T cells in viremic patients after stratification into those with low or high diversity (on the basis of median Shannon diversity). P values are generated by a nonparametric test based on Monte Carlo permutations (b, c) and by Mann–Whitney U test (d). VP, viremic patients without ID patients (n ¼ 22); ID, patients with CD4þ T-cell counts below 200 cells/ml (n ¼ 6); EC, elite controllers (n ¼ 3); CTR, healthy controls (n ¼ 9).

At baseline, the number of observed species correlated positively with CD4þ T-cell count (r ¼ 0.59, P ¼ 0.009), CD4þ% (r ¼ 0.54, P ¼ 0.02), CD4þ/CD8þ ratio (r ¼ 0.53, P ¼ 0.003), and negatively with LPS (r ¼ 0.51, P ¼ 0.007), LBP (r ¼ 0.45, P ¼ 0.01), sCD14 (r ¼ 0.42, P ¼ 0.02), and sCD163 (P ¼ 0.48, P ¼ 0.02) (Supplementary Table ST2, http://links.lww. com/QAD/A770). To further characterize the alpha diversity of the bacterial population in each participant, we calculated Shannon and Simpson index, respectively. At baseline, the Shannon index (P ¼ 0.04) and the Simpson index (P ¼ 0.02) were

significantly lower in HIV-1-infected patients compared to controls (Fig. 1c). Similarly to the observed species results, the individuals with the lowest CD4þ T-cell counts had the lowest alpha diversity (P ¼ 0.01). Furthermore, stratifying the patients at median Shannon index (5.68) revealed that the patients with lower alpha diversity had significantly lower CD4þ T-cell count (P ¼ 0.01) and CD4þ% (P ¼ 0.03) compared to patients with higher alpha diversity (Fig. 1d). In line with the observed species results, the Shannon alpha-diversity index correlated significantly with several parameters of HIV-1 progression and microbial translocation, although the correlations were slightly weaker (Supplementary

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Changes in gut microbiota in HIV-1 infection Nowak et al. Table 2. Number of observed species and Shannon alpha diversity as independent predictors of CD4R T-cell counts in viremic patients (n U 28). Number of observed species Predictor Covariates Age, Age, Age, Age, Age, Age, Age, Age,

sex sex, sex, sex, sex, sex, sex, sex,

ethnicity HIV-1 load BMI LPS LBP sCD14 sCD163

Beta-coefficient (95% CI) 0.88 0.85 0.84 1.02 0.74 0.88 0.73 0.92

(0.35–1.41) (0.30–1.39) (0.28–1.40) (0.42–1.61) (0.23–1.26) (0.30–1.46) (0.17–1.28) (0.31–1.53)

Shannon alpha diversity P value 0.002 0.004 0.005 0.002 0.007 0.005 0.013 0.005

Beta-coefficient (95% CI) 60.1 58.4 55.5 60.9 57.3 57.2 50.4 57.2

(13.5–106) (11.7–105) (6.52–104) (4.24–117) (17.5–97.2) (8.40–106) (5.81–95) (6.36–108)

P value 0.014 0.016 0.028 0.037 0.007 0.024 0.028 0.029

Beta-coefficients represent changes in CD4þ T-cell count for each unit increase in number of observed species and Shannon alpha diversity, respectively. Data are adjusted for age and sex in combination with a third covariate, added to the model one at the time. CI, confidence interval; LPS, lipopolysaccharide.

Table ST2, http://links.lww.com/QAD/A770). There was no correlation between the number of observed bacterial species or alpha diversity and levels of IL-6, Ddimer, age, sex, BMI, country of origin, or ethnicity.

Number of observed species and Shannon index are independent predictors of CD4R T-cell count in viremic patients Given the strong associations in the univariate analyses, we performed multivariate linear regression analyses with CD4þ T-cell count as dependent variable and observed species as well as Shannon index as predictors (Table 2). For every age and sex-adjusted increase in the number of bacterial species, the CD4þ T-cell count increased with 0.88 [95% confidence interval (CI) 0.35–1.41] units (P ¼ 0.002). Adding a third covariate (ethnicity, HIV-1 RNA load, BMI, LPS, LBP, sCD14, sCD163) to the model one at a time did not change the independent association between the observed bacterial species and the CD4þ T-cell count. LPS was the only covariate that was independently associated with CD4þ T-cell counts (adjusted beta ¼ 0.77, 95% CI 1.44, 0.11, P ¼ 0.025). In a model containing all covariates, LPS levels (P ¼ 0.037) and number of bacterial species (P ¼ 0.034) were the only factors independently associated with CD4þ T-cell counts. Similar results were seen for Shannon alpha diversity as a predictor of CD4þ T-cell counts (Table 2). Elite controllers have a lower interindividual variation in gut microbiota composition To compare the interindividual taxa differences among the groups, we calculated the beta diversity, using the weighted Unifrac and Bray–Curtis diversity indexes. The weighted Unifrac analysis revealed increased beta diversity in the HIV-1-infected patients at baseline as compared to the controls (P < 0.001), whereas the three elite controllers had the lowest beta diversity and hence the lowest interindividual variation (Fig. 2a). The Bray– Curtis diversity index analysis yielded similar results (data not shown). In principal coordinate analysis based on beta-diversity results, the three elite controllers clustered

along PC1 and PC2, whereas the gut microbiota of viremic patients and controls were overlapping (Fig. 2b).

Differences in microbiota composition between elite controllers and viremic patients Because of the distinct clustering of elite controllers in the beta diversity and PCoA analyses, we analyzed the microbiota composition in viremic patients (n ¼ 28) compared to both control individuals (n ¼ 9) and elite controllers (n ¼ 3). The most common phyla were Firmicutes, Bacteroidetes, and Actinobacteria, accounting for 94–95% of the overall microbes in all the groups (Fig. 2c). The most evident difference on phylum level was a higher relative abundance of Bacteroidetes in the elite controllers compared to the viremic patients (P ¼ 0.02), whereas Actinobacteria were enriched in viremic patients compared to the elite controllers (P ¼ 0.02). Among the less abundant phyla, there was an increased relative abundance of Proteobacteria in viremic patients compared to elite controllers (P ¼ 0.02). No significant differences were observed between viremic patients and control individuals on phylum level. On genus level, we could observe increased relative abundance of Lactobacillus in viremic patients compared to uninfected control individuals (P ¼ 0.002). Additionally, the genera of Lachnobacterium, Faecalibacterium, and Hemophilus were significantly reduced in viremic patients compared to control individuals (P ¼ 0.018, 0.008, and 0.04, respectively; Fig. 2d).

Reduction in alpha diversity after introduction of antiretroviral therapy After the introduction of ART, we found a moderate, yet significant decrease in the number of observed species (P ¼ 0.001) and Shannon index (P ¼ 0.006) compared to baseline (Fig. 3a). The changes of the bacterial taxa within the individuals were reflected by the overall significant (P < 0.001) increase in beta diversity (Fig. 3b). Additionally, the microbiota composition at follow-up changed for several taxa on phylum and genus level (Fig. 3c, d). Hence, genera of Lachnospira (P ¼ 0.002), Oribacterium

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