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PubMed2025

Absolute copy number aware CNV calling of sub-megabase segments in ultra-low coverage single-cell DNA sequencing data.

Recent advances in ultra-low coverage whole-genome sequencing (WGS) of single cells have enabled detailed analysis of copy number variation at a throughput approaching that of single-cell RNA sequencing. However, downstream computational methods have not seen comparable advances and are largely adaptations of deep sequencing methodology with reduced precision. Here, we present ASCENT, a computational method built to take full advantage of modern direct tagmentation-based WGS at ultra-low depth. Using joint segmentation with high-resolution bins, we accurately detect small segments, achieving accurate copy number profiles even at 100 000 reads per cell. ASCENT implements true absolute copy state inference for single cells, based on statistical modeling of coverage rather than comparison to a reference, while taking variable segment copy state into account. Further, ASCENT implements per-segment copy-neutral loss of heterozygosity (LOH) calling without the need for non-tumor or bulk WGS reference. When applied to a pediatric B-ALL sample, ASCENT finds copy-neutral LOH in a small segment and a minor subclone defined by breakpoints missed in bulk WGS. Thus, by applying appropriate computational methods, single-cell WGS provides clear advantages over bulk, even at a relatively low cell number and sequencing depth.

DNA Copy Number Variations↗

PubMed2026

Sequence optimization targeting mRNA stability enhances monoclonal antibody titers in CHO cells.

This study presents a DNA sequence optimization approach that integrates mRNA stability as a tunable design parameter to enhance monoclonal antibody expression in Chinese hamster ovary (CHO) cells. A comprehensive combinatorial library of synonymous coding-sequence variants of an IgG1 light chain was integrated as single copies at a defined genomic locus in CHO cells with identical regulatory elements. Steady-state mRNA abundance, quantified by deep sequencing of gDNA and mRNA, served as a proxy for mRNA stability. These data were used to train a machine learning model that predicts mRNA abundance from coding sequence using embeddings from a pre-trained nucleotide transformer. This abundance predictor, together with established translational metrics, was incorporated into a genetic algorithm for multi-objective codon optimization. As proof-of-concept, we optimized sequences encoding Trastuzumab to either maximize or minimize the abundance criterion and obtained benchmark sequences from two commercial providers. Using targeted integration, we generated CHO cell lines and measured protein titer and cell-specific productivity. Sequences optimized for high abundance significantly increased intracellular mRNA levels (+41%), protein titer (+59%), and cell-specific productivity (+85%) relative to low-abundance designs, while viable cell densities remained comparable. Compared to commercial benchmarks, high-abundance sequences achieved significantly higher titer (+70%) and cell-specific productivity (+98%). These findings establish mRNA stability as a practical and complementary design parameter for codon optimization in monoclonal antibody production, with potential applicability to other proteins and expression systems.

CHO↗

PubMed2026

ZILA-SRM: a probabilistic framework with zero-inflated latent models for robust strain reconstruction from metagenomes.

UNLABELLED: Resolving bacterial strain diversity from shotgun metagenomic data is fundamental to understanding intra-host evolution, transmission dynamics, and phenotypic heterogeneity. However, current probabilistic approaches face a severe "identifiability limit" when disentangling highly similar genomes. Under high-noise conditions, sequencing errors, coverage overdispersion, and collinearity confound standard expectation-maximization algorithms, resulting in overfitting and spurious "ghost" strains. Here, we introduce zero-inflated latent allocation for strain reconstruction from metagenomes with adaptive sparsity regularization (ZILA-SRM) to overcome this barrier through three innovations. First, we integrate a zero-inflated Poisson mixture model to decouple "structural zeros" (true strain absence) from "sampling zeros" (stochastic dropout), addressing overdispersion in standard Poisson-based tools. Second, we impose a convex adaptive sparsity regularization penalty that leverages biological sparsity priors to shrink noise artifacts dynamically. Third, we implement a graph-theoretic refinement step using maximal clique enumeration to resolve haplotype collinearity. Benchmarking against StrainFinder and MixtureS on 702 synthetic data sets shows that ZILA-SRM achieves a 20% improvement in precision in high-complexity scenarios while maintaining over 80% recall for minor variants at 0.5% abundance. Re-analysis of deep-sequencing data from 195 Mycobacterium tuberculosis clinical samples reveals cryptic low-abundance drug-resistant variants in 12% of patients, including a minor clone carrying the rpoB S450L mutation. Furthermore, application to skin microbiome data sets further reveals a strong negative correlation between dominant Staphylococcus aureus and Staphylococcus epidermidis strains, providing genomic evidence for competitive exclusion. These findings establish ZILA-SRM as a robust tool for resolving strain-level diversity in complex metagenomes. IMPORTANCE: Understanding microbial communities at the strain level is critical because closely related strains can differ dramatically in traits such as drug resistance, virulence, and ecological interactions. However, resolving individual strains from metagenomic sequencing data remains difficult, especially when strains are highly similar or present at low abundance. As a result, biologically meaningful diversity is often obscured or misinterpreted as noise. In this study, we introduce a new framework that improves the reliability of strain reconstruction from complex metagenomic data. By reducing false-positive strain detection while preserving sensitivity to rare variants, our approach enables more accurate characterization of microbial populations. This improved resolution reveals previously hidden subpopulations in clinical and microbiome datasets, providing clearer insights into microbial evolution, competition, and the emergence of clinically relevant traits such as antibiotic resistance.

Metagenomics↗

PubMed2019

Histone H3 lysine K4 methylation and its role in learning and memory.

Epigenetic modifications such as histone methylation permit change in chromatin structure without accompanying change in the underlying genomic sequence. A number of studies in animal models have shown that dysregulation of various components of the epigenetic machinery causes cognitive deficits at the behavioral level, suggesting that proper epigenetic control is necessary for the fundamental processes of learning and memory. Histone H3 lysine K4 (H3K4) methylation comprises one component of such epigenetic control, and global levels of this mark are increased in the hippocampus during memory formation. Modifiers of H3K4 methylation are needed for memory formation, shown through animal studies, and many of the same modifiers are mutated in human cognitive diseases. Indeed, all of the known H3K4 methyltransferases and four of the known six H3K4 demethylases have been associated with impaired cognition in a neurologic or psychiatric disorder. Cognitive impairment in such patients often manifests as intellectual disability, consistent with a role for H3K4 methylation in learning and memory. As a modification quintessentially, but not exclusively, associated with transcriptional activity, H3K4 methylation provides unique insights into the regulatory complexity of writing, reading, and erasing chromatin marks within an activated neuron. The following review will discuss H3K4 methylation and connect it to transcriptional events required for learning and memory within the developed nervous system. This will include an initial discussion of the most recent advances in the developing methodology to analyze H3K4 methylation, namely mass spectrometry and deep sequencing, as well as how these methods can be applied to more deeply understand the biology of this mark in the brain. We will then introduce the core enzymatic machinery mediating addition and removal of H3K4 methylation marks and the resulting epigenetic signatures of these marks throughout the neuronal genome. We next foray into the brain, discussing changes in H3K4 methylation marks within the hippocampus during memory formation and retrieval, as well as the behavioral correlates of H3K4 methyltransferase deficiency in this region. Finally, we discuss the human cognitive diseases connected to each H3K4 methylation modulator and summarize advances in developing drugs to target them.

Animals↗

PubMed2025

ChIP-Rx: Arabidopsis Chromatin Profiling Using Quantitative ChIP-Seq.

Chromatin immunoprecipitation followed by deep sequencing (ChIP-seq) is widely used to probe the chromatin landscape of transcription factors, chromatin components, and associated proteins. Conventional ChIP normalization procedures robustly allow estimating differences in local enrichment across genomic regions. Yet, inter-sample comparisons can be biased by technical variability and biological differences. This is notably the case when samples display large differences in the abundance of the target protein or its enrichment at chromatin. For example, epigenome defects are improperly detected or quantified upon large-effect genetic or chemical inhibition of chromatin modifiers. To circumvent these caveats and robustly determine biological variations while minimizing technical variability, ChIP adaptations using an external reference have flourished. Here, we describe a step-by-step protocol employing a reference exogenous chromatin (ChIP-Rx) that allows absolute comparisons of epigenome variations in Arabidopsis samples displaying drastic differences in chromatin mark abundance. In contrast to the originally published ChIP-Rx approach, which assumes that exogenous spike-in references are constant across samples, the method detailed here involves the sequencing of each input sample to account for technical variability in initial reference chromatin contents. We also report a detailed computational workflow with an accompanying Github resource to help in calculating spike-in normalization factors, applying them to normalize epigenome tracks, and performing spike-in normalized inter-sample differential analyses. We propose two ways of computing the spike-in factor: a classically used method based on raw counts and a noise-corrected method using peak detection on the exogenous genome.

Arabidopsis↗

PubMed2026

Collateral sensitivity-harnessing microbial vulnerabilities as a solution to antimicrobial resistance.

Bacteria exhibit an evolutionary trade-off through their development of collateral sensitivity (CS) which allows them to resist one antibiotic while becoming more vulnerable to another. This vulnerability offers a compelling therapeutic opportunity by selecting against resistant isolates. Laboratory evolution studies, genome sequencing, deep mutagenesis and use of artificial intelligence and machine learning can design the bespoke strategy against multi-drug-resistant bacteria. This review discusses about recent studies that are rationally designed to harness this evolutionary trade-off for the development of alternative antimicrobial strategies. The translational barriers to the clinical implementation of CS are addressed and evidence-based design principles for optimization of CS-guided therapy are discussed.

Bacteria↗

PubMed2026

Identification of genetic determinants that promote biofilm growth under heterotrophic conditions in Cupriavidus necator using transposon enrichment.

Cupriavidus necator is a metabolically versatile β-proteobacterium of growing interest for auto- and heterotrophic bioprocesses, yet the genetic determinants governing its biofilm formation remain largely uncharacterized, particularly under process-relevant heterotrophic conditions. Here, we applied a forward-genetics transposon-enrichment approach to identify loci which promote surface-associated growth. A high-density mini-Tn5 mutant library (26,185 insertion clones, exceeding the >17,000 required for genome-wide coverage) was cultivated as a biofilm in a microfluidic flow-cell system on fructose for 168 h, and the surface-associated community was characterized by deep sequencing. Twelve genes showed significantly elevated insertion frequencies, several with documented links to biofilm formation in other bacteria, including the ferrous-iron uptake system (feoA/feoB), galU, and a GSDEF/EAL dual-domain protein. The gene B2043 (E6A55_RS29530), encoding this c-di-GMP-metabolizing protein, was selected for validation by markerless deletion. Under static conditions, the ΔB2043 mutant showed a 1.69 ± 0.06-fold increase in biofilm-associated biomass (p = 5.16 × 10-15). Under flow-through conditions, the mutant attached faster, entered exponential growth ∼10 h earlier, reached its biovolume plateau ∼16 h earlier than the wild-type, and formed distinct tower-like structures. These results identify B2043 as a negative regulator of biofilm formation acting predominantly during attachment, provide the first experimental evidence for c-di-GMP-dependent biofilm regulation in C. necator H16, and establish a functional-genomics framework - together with eleven further candidate loci - for engineering productive biofilms in this organism.

Biofilm formation↗

PubMed2026

Detection of antibiotic heteroresistance in clinical microbiology: current and emerging methodologies.

BACKGROUND: Antibiotic heteroresistance (HR) is characterised by the coexistence of susceptible and resistant subpopulations within an apparently isogenic bacterial isolate. Because routine antimicrobial susceptibility testing (AST) primarily assesses the dominant population, HR may escape detection, potentially leading to discrepancies between laboratory susceptibility categorisation and the underlying bacterial population structure. OBJECTIVES: To provide a critical and practice-oriented evaluation of current and emerging methodologies for HR detection and to discuss their strengths, limitations, and potential for clinical implementation. SOURCES: Narrative review based on PubMed searches, complemented by screening of key reference lists and relevant EUCAST and CLSI documents. Peer-reviewed literature was prioritised. CONTENT: Phenotypic approaches, particularly population analysis profiling, remain the reference method for HR definition, but their labour-intensive workflows, long turnaround times, and limited standardisation restrict routine implementation. Alternative strategies, including modified AST assays, metabolic assays, and single-cell platforms, offer gains in speed or throughput but require broader validation. Molecular approaches such as quantitative PCR, droplet digital PCR, targeted deep sequencing, and whole-genome sequencing improve detection of minority resistance determinants. Emerging computational frameworks, including machine learning models integrating phenotypic and genomic data, represent a promising frontier for scalable HR prediction. IMPLICATIONS: Available evidence supports the clinical relevance of HR, although its association with adverse outcomes varies across bacterial species and antibiotic classes. Harmonised methodologies and clinically validated interpretive criteria are needed to support integration of HR assessment into routine diagnostics. Prospective multicentre studies and further standardisation, including engagement with EUCAST and CLSI, will be important to advance clinical implementation.

Antimicrobial resistance↗

PubMed2026

TNFα-dependent modulation of WT1-MMP9 regulatory axis links developmental and inflammatory pathways in glaucoma.

Glaucomas are heterogeneous optic neuropathies associated with extracellular matrix dysregulation, abnormal ocular morphogenesis, and inflammatory signaling. Targeted deep sequencing of 586 primary congenital glaucoma (PCG) cases and 1,757 controls identified rare pathogenic variants in multiple genes, including WT1 and MMP9. Notably, WT1 variants clustered within the nuclear export sequence. Further, functional analyses showed that combined wt1-pax6 suppression in zebrafish disrupted ocular morphogenesis, highlighting developmental interdependence. In human trabecular meshwork cells, WT1 acted as a transcriptional repressor of MMP9, while TNF-α signaling triggered nitric oxide-dependent nuclear export of WT1, resulting in delayed MMP9 upregulation. This effect was reversible by inhibiting nuclear export or nitric oxide synthase. A patient-derived mutation in the nuclear-export region of WT1, disrupted this regulatory switch, causing abnormal MMP9 expression. These findings position WT1 as an important regulator linking developmental and inflammatory mechanisms in glaucoma pathogenesis.

anterior segment dysgenesis↗

PubMed2026

Postzygotic biallelic inactivation of FDFT1 underlies solitary lesion formation in porokeratosis of Mibelli.

BACKGROUND: Porokeratosis reflects clonal expansion of keratinocytes with biallelic inactivation of mevalonate-cholesterol biosynthesis pathway genes. In disseminated porokeratosis (DP), lesions arise through independent somatic second hits in carriers of heterozygous germline pathogenic variants, whereas porokeratosis of Mibelli (PM) is usually solitary, and its molecular basis remains incompletely defined. OBJECTIVE: To elucidate the molecular basis of solitary PM. METHODS: We analyzed blood and lesional epidermis from seven patients with solitary PM within a 156-patient porokeratosis cohort using deep sequencing, copy-number/SNP profiling, and methylation analysis. RESULTS: Solitary PM plaques were larger and more irregular than the annular DP lesions. No pathogenic germline variants were detected in MVK, PMVK, MVD, FDPS, or FDFT1. Three patients had somatic biallelic genetic inactivation of FDFT1 through putative deleterious variants and/or focal microdeletions. The remaining four showed FDFT1 promoter hypermethylation with loss of heterozygosity (LOH) at the FDFT1 locus due to copy-neutral LOH or a monoallelic 8p deletion, consistent with early monoallelic epigenetic silencing, followed by genetic loss of the remaining active allele. In one patient, part of the plaque expanded centrifugally over 7.5 years. CONCLUSION: Solitary PM can be driven by postzygotic, lesion-restricted, biallelic inactivation of FDFT1 through genetic or epigenetic mechanisms within a single epidermal clone, promoting clonal expansion. This model may explain the tendency toward solitary PM lesions. The low probability of acquiring postzygotic biallelic inactivation without germline predisposition may underlie solitary PM and suggest a low recurrence risk for offspring, unlike DP driven by germline heterozygosity.

General dermatology↗

PubMed2025

ctDNA can detect minimal residual disease in curative treated non-small cell lung cancer patients using a tumor agnostic approach.

BACKGROUND: Circulating tumor DNA (ctDNA) has the potential to become a reliable biomarker for identifying minimal residual disease (MRD) and predicting recurrence in patients with non-small cell lung cancer (NSCLC) following curative treatment. However, there is a lack of studies that investigate the clinical validity of ctDNA using a tumor-agnostic approach, which can provide significant clinical benefits. METHODS: We analyzed samples from 45 NSCLC patients recruited in a prospective national multicenter study, all of whom had undergone curative treatment. A total of 38 pre-treatment plasma samples and 76 post-treatment plasma samples were examined using a commercially available cancer personalized profiling by deep sequencing (CAPP-seq) strategy, and a tumor-agnostic approach. Post-treatment samples were collected at two distinct landmark time points: Follow-up 1 (0.5-4.5 months post-treatment) and Follow-up 2 (4.5-7.5 months post-treatment). RESULTS: Detectable ctDNA post-treatment was significantly associated with increased risk of tumor recurrence and shorter recurrence-free survival (RFS). Using only a single blood sample taken from Follow-up 2, we correctly identified MRD in 50% of the patients who later experienced recurrence. However, subgroup analysis further revealed that in patients treated with radiotherapy or chemoradiotherapy (CRT), ctDNA detection was significantly linked to shorter RFS in the MRD analysis from Follow-up 2, but not in the MRD analysis from Follow-up 1. CONCLUSION: These findings suggest that post-treatment ctDNA, detected using a tumor-agnostic approach, is a reliable biomarker for predicting recurrence in NSCLC patients following curative treatment. However, the optimal timing for blood sampling to detect MRD appears to depend on the type of curative treatment received.

Humans↗

PubMed2026

Pervasive noise in human pre-mRNA splice site selection.

RNA splicing has historically been thought to be highly efficient and accurate, with little opportunity for deviation from regulated alternative splicing. This dogma has been challenged by recent observations that biological noise may contribute substantially to transcriptome diversity. However, quantitative understanding of stochastic splicing variation is challenging because these transcripts are likely subject to rapid degradation. Here, we use deep sequencing across RNA compartments to track splicing intermediates in human cells and see abundant cryptic splicing associated with genomic features that promote splicing noise. We observe pervasive usage of low-fidelity splice sites, likely due to stochasticity in recruitment or binding of the spliceosome. These sites are turned over quickly and show evidence for nuclear and cytoplasmic degradation, suggesting widespread surveillance and rapid quality control of non-productive transcripts. Our findings provide insights into the propensity for error in RNA processing mechanisms and regulation of alternative splice sites across a gene.

Humans↗

PubMed2026

A muskrat tissue atlas of small non-coding RNAs and their regulatory roles in muskrat musk secretion.

Muskrat musk, secreted by the male muskrat scent gland during the secretion period, is a valuable natural product with promising pharmacological activities. Its synthesis is regulated not only by coding genes but also by small non-coding RNAs (sncRNAs). However, a comprehensive tissue atlas of sncRNAs in muskrats has been lacking. To address this issue, we systematically profiled the expression levels of 6 sncRNA categories (piRNA [PIWI-interacting RNA], miRNA [microRNA], snoRNA [small nucleolar RNA], snRNA [small nuclear RNA], tRNA [transfer RNA], and other RNAs) across 13 tissues of the muskrat via deep sequencing. We identified 23,957 sncRNAs (∼ 65%) exhibiting tissue-specific expression patterns throughout the body. The results show that miRNA is the main contributor to tissue specificity. Eleven tissues showed a significantly higher number of miRNA-5p arm expressions compared to the 3p arm, although the brain was an exception. Quantitative results imply that miR-477-3p/5p and miR-794-3p are potentially involved in the regulation of muskrat musk synthesis and secretion in the muskrat scent glands. Their target genes were enriched in pathways related to energy supply, lipid metabolism, and cyclic morphological changes of the scent gland. Furthermore, we constructed a set of co-expressed miRNAs based on the hormone-dominated "brain-testis-scent gland" axis and the energy metabolism-dominated "brain-liver-scent gland" axis. These results provide the most comprehensive description to date of tissue-specific and ubiquitous sncRNAs in individual muskrat tissues. We anticipate that these data will enhance the understanding of the molecular regulation underlying muskrat musk synthesis and secretion.

Animals↗

PubMed2017

Genome-wide analysis suggests a differential microRNA signature associated with normal and diabetic human corneal limbus.

Small non-coding RNAs, in particular microRNAs (miRNAs), regulate fine-tuning of gene expression and can impact a wide range of biological processes. However, their roles in normal and diseased limbal epithelial stem cells (LESC) remain unknown. Using deep sequencing analysis, we investigated miRNA expression profiles in central and limbal regions of normal and diabetic human corneas. We identified differentially expressed miRNAs in limbus vs. central cornea in normal and diabetic (DM) corneas including both type 1 (T1DM/IDDM) and type 2 (T2DM/NIDDM) diabetes. Some miRNAs such as miR-10b that was upregulated in limbus vs. central cornea and in diabetic vs. normal limbus also showed significant increase in T1DM vs. T2DM limbus. Overexpression of miR-10b increased Ki-67 staining in human organ-cultured corneas and proliferation rate in cultured corneal epithelial cells. MiR-10b transfected human organ-cultured corneas showed downregulation of PAX6 and DKK1 and upregulation of keratin 17 protein expression levels. In summary, we report for the first time differential miRNA signatures of T1DM and T2DM corneal limbus harboring LESC and show that miR-10b could be involved in the LESC maintenance and/or their early differentiation. Furthermore, miR-10b upregulation may be an important mechanism of corneal diabetic alterations especially in the T1DM patients.

Adult↗

PubMed2016

Deletion of Indian hedgehog gene causes dominant semi-lethal Creeper trait in chicken.

The Creeper trait, a classical monogenic phenotype of chicken, is controlled by a dominant semi-lethal gene. This trait has been widely cited in the genetics and molecular biology textbooks for illustrating autosomal dominant semi-lethal inheritance over decades. However, the genetic basis of the Creeper trait remains unknown. Here we have utilized ultra-deep sequencing and extensive analysis for targeting causative mutation controlling the Creeper trait. Our results indicated that the deletion of Indian hedgehog (IHH) gene was only found in the whole-genome sequencing data of lethal embryos and Creeper chickens. Large scale segregation analysis demonstrated that the deletion of IHH was fully linked with early embryonic death and the Creeper trait. Expression analysis showed a much lower expression of IHH in Creeper than wild-type chickens. We therefore suggest the deletion of IHH to be the causative mutation for the Creeper trait in chicken. Our findings unravel the genetic basis of the longstanding Creeper phenotype mystery in chicken as the same gene also underlies bone dysplasia in human and mouse, and thus highlight the significance of IHH in animal development and human haploinsufficiency disorders.

Animals↗

PubMed2025

Pervasive noise in human splice site selection.

RNA splicing has historically been thought to be highly efficient and accurate, with little opportunity for deviation from regulated alternative splicing decisions. This dogma has been challenged by recent observations that suggest that biological noise may contribute substantially to transcriptome diversity. However, quantitative understanding of stochastic variations in splicing is challenging because these transcripts are likely subject to rapid degradation. Here, we use ultra-deep sequencing across RNA compartments to track splicing intermediates in human cells and see abundant cryptic splicing associated with genomic features that promote splicing noise. We observe pervasive usage of low-fidelity splice sites, likely due to stochasticity in recruitment or binding of the spliceosome. These sites are most likely degraded in the nucleus rather than targeted by translation-dependent degradation processes, suggesting widespread surveillance and rapid quality control of non-productive RNA transcripts. Our findings provide unprecedented insights into the propensity for error in RNA processing mechanisms and the regulation of alternative splice sites across a gene.

Journal Article↗

PubMed2025

A single-cell transcriptomic atlas of the pigtail macaque placenta in late gestation.

The placenta is a complex organ with multiple immune and non-immune cell types that promote fetal tolerance and facilitate the transfer of nutrients and oxygen. The nonhuman primate (NHP) is a key experimental model for studying human pregnancy complications, in part due to similarities in placental structure, which makes it essential to understand how single-cell populations compare across the human and NHP maternal-fetal interface. We constructed a single-cell RNA-Seq (scRNA-Seq) atlas of the placenta from the pigtail macaque ( Macaca nemestrina ) in the third trimester, comprising three different tissues at the maternal-fetal interface: the chorionic villi (placental disc), chorioamniotic membranes, and the maternal decidua. Each tissue was separately dissociated into single cells and processed through the 10X Genomics and Seurat pipeline, followed by aggregation, unsupervised clustering, and cluster annotation. Next, we determined the maternal-fetal origins of cell populations and analyzed single-cell RNA trajectory, Gene Ontology enrichment, and cell-cell communication. Single-cell populations in the pigtail macaque were strikingly similar in their identity and frequency to those found in the human placenta, including cells from trophoblast, stromal cell, immune, and macrophage lineages. An advantage of our approach was the deep sequencing of three tissues at the maternal-fetal interface, which yielded a rich diversity of common and rare single-cell populations. The third-trimester pigtail macaque single-cell atlas enables the identification of cellular subclusters analogous to those in humans and provides a powerful resource for understanding experimental perturbations on the NHP placenta.

Journal Article↗

PubMed2025

Patterns of HIV-1 viral load suppression and drug resistance during the dolutegravir transition: a population-based longitudinal study.

BACKGROUND: Data on the population-scale impact of dolutegravir (DTG)-based HIV regimens in sub-Saharan Africa are extremely limited. We used data from a surveillance cohort in southern Uganda to assess viral suppression and antiretroviral (ART) resistance over 10-years alongside DTG scale-up. METHODS: Consenting participants in the population-based Rakai Community Cohort Study between August 2011 and March 2023 aged 15-59 completed questionnaires and provided samples for HIV testing, viral load quantification, and viral deep-sequencing. We collected data on DTG-utilization at HIV care clinics. We estimated the prevalence of HIV suppression (<1,000 copies/mL) and ART resistance using robust Poisson regression. Bayesian logistic regression quantified associations between resistance and individual-level suppression across surveys. FINDINGS: Among 20,383 people living with HIV (PLHIV), suppression increased from 57.1% (95% confidence interval [CI]: 55.4%-58.8%) to 90.3% (95%CI: 89.2%-91.4%) between 2014 and 2022. By 2020 84.4% (95%CI: 83.7%-85.2%) and 64.6% (95%CI: 63.9%-65.3%) of men and women were on DTG regimens. Among treatment-experienced viremic PLHIV, overall resistance decreased from 51.1% (95%CI: 40.7%-64.1%, 2014) to 27.9% (95%CI: 21.3%-36.5%, 2022). Only two participants harbored intermediate/high-level DTG resistance, attributable to inQ148R, inE138K, and inG140A. Low-level INSTI resistance (inS153Y) was observed in 23/207 (7.5%) of viremic individuals, with putative evidence of transmission. By 2022, suppression was unrelated to prior history of NNRTI/NRTI resistance (risk ratios: 1.14, 95%HPD: 0.96-1.32 and 1.12, 95%HPD: 0.88 - 1.35). INTERPRETATION: Viral suppression increased during the DTG-transition with minimal emerging intermediate/high-level resistance. Falling resistance among treatment-experienced PLHIV underscores the role of ART adherence in reducing viremia. The emergence of inS153Y justifies continued genomic surveillance of ART resistance. FUNDING: National Institutes of Health and the Gates Foundation.

Journal Article↗