Publications: HIV
Machine Learning Bolsters Evidence That D1, Nef, and Tat Influence HIV Reservoir Dynamics
Abstract: The primary hurdle to curing HIV is due to the establishment of a reservoir early in infection. In an effort to find new treatment strategies, we and others have focused on understanding the selection pressures exerted on the reservoir by studying how proviral sequences change over time. To gain insights into the dynamics of the HIV reservoir we analyzed longitudinal near full-length sequences from 7 people living with HIV between 1 and 20 years following the initiation of antiretroviral treatment. We used this data to employ Bayesian mixed effects models to characterize the decay of the reservoir using single-phase and multiphasic decay models based on near full-length sequencing. In addition, we developed a machine-learning approach utilizing logistic regression to identify elements within the HIV genome most associated with proviral decay and persistence. By systematically analyzing proviruses that are deleted for a specific element, we gain insights into their role in reservoir contraction and expansion.
Our analyses indicate that biphasic decay models of intact reservoir dynamics were better than single-phase models with a stronger statistical fit. Based on the biphasic decay pattern of the intact reservoir, we estimated the half-lives of the first and second phases of decay to be 18.2 (17.3 to 19.2, 95%CI) and 433 (227 to 6400, 95%CI) months, respectively.In contrast, the dynamics of defective proviruses differed favoring neither model definitively, with an estimated half-life of 87.3 (78.1 to 98.8, 95% CI) months during the first phase of the biphasic model. Machine-learning analysis of HIV genomes at the nucleotide level revealed that the presence of the splice donor site D1 was the principal genomic element associated with contraction. This role of D1 was then validated in an in vitro system. Using the same approach, we additionally found supporting evidence that HIV nef may confer a protective advantage for latently infected T cells while tat was associated with clonal expansion. The nature of intact reservoir decay suggests that the long-lived HIV reservoir contains at least 2 distinct compartments. The first compartment decays faster than the second compartment. Our machine-learning analysis of HIV proviral sequences reveals specific genomic elements are associated with contraction while others are associated with persistence and expansion. Together, these opposing forces shape the reservoir over time.
Highlights from the Inaugural HIV Reservoirs and Immune Control Conference, October 1st-4th 2023, Malahide Ireland
Abstract: The inaugural FASEB HIV Reservoirs and Immune Control Conference brought researchers together from across the globe to discuss reservoir dynamics in clinical cohorts. It extended over 4 days in the seaside town of Malahide, Ireland. The scientific sessions covered a broad range of topics, including: 1) HIV pathogenesis and control, 2) reservoirs and viral expression, 3) pediatric reservoirs, 4) innate immunity and B cell responses, 5) environmental factors affecting pathogenesis, 6) loss of virologic control, and 7) HIV-2. The following article provides a brief summary of the meeting proceedings and includes a supplementary document with the meeting abstracts.
Naive infection predicts reservoir diversity and is a formidable hurdle to HIV eradication
Abstract: Historically, naive cells have been considered inconsequential to HIV persistence. Here, we compared the contributions of naive and memory cells to the reservoirs of individuals with a spectrum of reservoir sizes and variable immunological control. We performed proviral sequencing of approximately 6000 proviruses from cellular subsets of 5 elite controllers (ECs) off antiretroviral therapy (ART) and 5 chronic progressors (CPs) on ART. The levels of naive infection were barely detectable in ECs and approximately 300-fold lower compared with those in CPs. Moreover, the ratio of infected naive to memory cells was significantly lower in ECs. Overall, the naive infection level increased as reservoir size increased, such that naive cells were a major contributor to the intact reservoir of CPs, whose reservoirs were generally very diverse. In contrast, the reservoirs of ECs were dominated by proviral clones. Critically, the fraction of proviral clones increased with cell differentiation, with naive infection predicting reservoir diversity. Longitudinal sequencing revealed that the reservoir of ECs was less dynamic compared with that of CPs. Naive cells play a critical role in HIV persistence. Their infection level predicts reservoir size and diversity. Moreover, the diminishing diversity of the reservoir as cellular subsets mature suggests that naive T cells repopulate the memory compartment and that direct infection of naive T cells occurs in vivo.
Persistence of an intact HIV reservoir in phenotypically naive T cells
Abstract: Despite the efficacy of antiretroviral therapy (ART), HIV persists in a latent form and remains a hurdle to eradication. CD4+ T lymphocytes harbor the majority of the HIV reservoir, but the role of individual subsets remains unclear. CD4+ T cells were sorted into central, transitional, effector memory, and naive T cells. We measured HIV DNA and performed proviral sequencing of more than 1900 proviruses in 2 subjects at 2 and 9 years after ART initiation to estimate the contribution of each subset to the reservoir. Although our study was limited to 2 subjects, we obtained comparable findings with publicly available sequences. While the HIV integration levels were lower in naive compared with memory T cells, naive cells were a major contributor to the intact proviral reservoir. Notably, proviral sequences isolated from naive cells appeared to be unique, while those retrieved from effector memory cells were mainly clonal. The number of clones increased as cells differentiated from a naive to an effector memory phenotype, suggesting naive cells repopulate the effector memory reservoir as previously shown for central memory cells. Naive T cells contribute substantially to the intact HIV reservoir and represent a significant hurdle for HIV eradication.
Next-Generation Sequencing in a Direct Model of HIV Infection Reveals Important Parallels to and Differences from In Vivo Reservoir Dynamics
Abstract: Next-generation sequencing (NGS) represents a powerful tool to unravel the genetic make-up of the HIV reservoir, but limited data exist on its use in vitro Moreover, most NGS studies do not separate integrated from unintegrated DNA, even though selection pressures on these two forms should be distinct. We reasoned we could use NGS to compare the infection of resting and activated CD4 T cells in vitro to address how the metabolic state affects reservoir formation and dynamics. To address these questions, we obtained HIV sequences 2, 4, and 8 days after NL4-3 infection of metabolically activated and quiescent CD4 T cells (cultured with 2 ng/ml interleukin-7). We compared the composition of integrated and total HIV DNA by isolating integrated HIV DNA using pulsed-field electrophoresis before performing sequencing. After a single-round infection, the majority of integrated HIV DNA was intact in both resting and activated T cells. The decay of integrated intact proviruses was rapid and similar in both quiescent and activated T cells. Defective forms accumulated relative to intact ones analogously to what is observed in vivo Massively deleted viral sequences formed more frequently in resting cells, likely due to lower deoxynucleoside triphosphate (dNTP) levels and the presence of multiple restriction factors. To our surprise, the majority of these deleted sequences did not integrate into the human genome. The use of NGS to study reservoir dynamics in vitro provides a model that recapitulates important aspects of reservoir dynamics. Moreover, separating integrated from unintegrated HIV DNA is important in some clinical settings to properly study selection pressures.
Longitudinal HIV sequencing reveals reservoir expression leading to decay which is obscured by clonal expansion
Abstract: After initiating antiretroviral therapy (ART), a rapid decline in HIV viral load is followed by a long period of undetectable viremia. Viral outgrowth assay suggests the reservoir continues to decline slowly. Here, we use full-length sequencing to longitudinally study the proviral landscape of four subjects on ART to investigate the selective pressures influencing the dynamics of the treatment-resistant HIV reservoir. We find intact and defective proviruses that contain genetic elements favoring efficient protein expression decrease over time. Moreover, proviruses that lack these genetic elements, yet contain strong donor splice sequences, increase relatively to other defective proviruses, especially among clones. Our work suggests that HIV expression occurs to a significant extent during ART and results in HIV clearance, but this is obscured by the expansion of proviral clones. Paradoxically, clonal expansion may also be enhanced by HIV expression that leads to splicing between HIV donor splice sites and downstream human exons.
Publications: Transfusion Medicine
Red cell exchange for rapid leukoreduction in adults with hyperleukocytosis and leukostasis
Abstract: We show for the first time that red cell exchange (RCE) treats hyperleukocytosis in acute leukemia. RCE provided similar leukoreduction to standard therapeutic leukoreduction and could be superior in patients with severe anemia, monocytic leukemias, or when requiring rapid treatment.
More efficient exchange of sickle red blood cells can be achieved by exchanging the densest red blood cells: An ex vivo proof of concept study
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Background: In sickle cell disease (SCD), red blood cells (RBCs) containing hemoglobin S can be denser than RBCs containing wild-type hemoglobin, especially when dehydrated. We hypothesize that targeting denser RBCs during red blood cell (RBC) exchange for SCD could result in more efficient removal of dehydrated, sickled RBCs and preservation of non-sickled RBCs.
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Study design and methods: Waste products from RBC exchanges for SCD were used as "simulated patients". One RBC volume was exchanged using ABO-compatible blood. The apheresis instrument was programmed to exchange the entire RBC layer by indicating the hematocrit (control), or the bottom half by indicating the hematocrit was half the hematocrit (experimental), with or without subsequent transfusion. Hemoglobin S levels, and complete blood counts were measured.
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Results: Hemoglobin S levels were lower after the modified versus control RBC exchange (post-RBC exchange mean 4.96% and 11.27%); total hemoglobin S amounts were also lower (mean 19.27 and 58.29 mL of RBCs). Mean RBC density decreased after the modified RBC exchange by 8.86%. Hematocrit decreased in the modified RBC exchange by 36.37%, with partial correction by direct transfusion following a truncated RBC exchange.
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Conclusions: Targeting denser RBCs in RBC exchange enhanced hemoglobin S removal and decreased RBC density. Further development of this ex vivo model could potentially allow for: 1) improved reduction in hemoglobin S levels (allowing for longer periods between RBC exchange or maintained lower levels), or 2) achievement of previous goal hemoglobin S levels with fewer donor units (reducing alloimmunization risk and improving blood utilization).
Rapid prediction of stem cell mobilization using volume and conductivity data from automated hematology analyzers
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Background: Rapid analytics to predict circulating hematopoietic stem cells are valuable for optimal management of mobilization, particularly for the use of newer and costly mobilization agents such as plerixafor.
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Study design and methods: We used stepwise, linear multiple regression modeling applied to cell population data collected by routine hematology analyzers (Beckman Coulter DxH 800) on patients undergoing autologous stem cell collection (n = 131). Beta coefficients were used to derive a formula for a stem cell index (SCI). We then tested the correlation of SCI with stem cell counts and performance of the SCI as a predictor of poor mobilization with external validation in a separate cohort (n = 183).
Results: The SCI correlated strongly with CD34 counts by flow cytometry (r = 0.8372 in the development cohort, r = 0.8332 in the external validation cohort) and compares favorably with other rapid stem cell enumerating technologies. In the external validation cohort, the SCI performed well as a predictor (receiver operating characteristic area under the curve, 0.9336) of poor mobilization (CD34 count < 10), with a sensitivity of 72% and a specificity of 93%. When prevalence of poor mobilization was 33%, this resulted in a positive predictive value of 83% and a negative predictive value of 87%. The SCI also showed promise in tracking responses to plerixafor administration.
Conclusion: The findings demonstrate the utility of the cell population data collected by hematology analyzers to provide rapid data beyond standard complete blood counts, particularly for stem cell count prediction, requiring no additional reagents, specimen, or instrumentation.