Biology subjects

Verma, S.

Publications and source records attributed to Verma, S..

At least 19 recordsLinked to original sources

bioRxiv2026

KIF1A-driven entry of degradative lysosomes into the axon is developmentally regulated by the microtubule environment at the axon initial segment

Neuronal function requires precise transport of lysosomal vesicles along highly polarized processes, yet how this trafficking is spatially and developmentally regulated remains poorly understood. Here, we show that the neuronally enriched kinesin-3 motor KIF1A is required for dendritic and axonal localization of lysosomal vesicles in both immature and mature rat hippocampal neurons. Remarkably, the specialized microtubule environment of the axon initial segment (AIS) restricts KIF1A-driven transport of degradative, cathepsin D-positive lysosomal vesicles while permitting less degradative lysosomal vesicles to enter axons in mature neurons. Disrupting the AIS microtubule environment or expressing a hereditary spastic paraplegia type 30-associated KIF1A variant with increased affinity for GTP-tubulin bypasses this restriction, enabling degradative lysosomal vesicles to enter mature axons. In human iPSC-derived neurons, KIF1A depletion similarly disrupts axonal lysosomal vesicle transport, causes autophagic vesicle accumulation, and triggers axonal degeneration. Together, our findings reveal a developmentally regulated AIS gate that selectively controls KIF1A-driven lysosomal vesicle transport into axons and link its subversion to KIF1A-associated neurological disease.

cell biology↗

bioRxiv2026

Limits of marker information transfer]{Limits of marker information transfer in cross-panel cytometry imputation

Marker imputation can bridge cytometry datasets acquired with different panels and platforms. Its validity depends on whether common markers retain information about unmeasured target markers and whether those relationships transfer across assay contexts. We evaluated these limits in two paired flow cytometry-CyTOF cohorts comprising 134 patients and 257 specimens. A patient-held-out framework distinguished within-platform same-cell reconstruction from cross-platform distribution translation without cell correspondence. We compared conventional machine-learning and deep generative estimators with median imputation and used permutation controls to estimate the contributions of patient matching and source-exclusive markers. Evaluation covered marker values, specimen distributions, phenotype utility, and directional predictive relationships among markers. Within platforms, exact k-nearest neighbors reduced mean absolute error by 12.8-35.0% relative to median imputation. However, the median-based reconstructions were contracted, with a median ratio of predicted to observed interquartile range below 1 in every context and evaluable population. Patient matching improved cross-platform distribution recovery, whereas adding source-exclusive markers or higher-capacity estimators did not consistently produce net gains. In the independently annotated acute myeloid leukemia (AML) cohort, reconstructed markers largely preserved broad-lineage classification but did not recover fine-phenotype information available through direct measurement. In AML-CyTOF, the measured full panel outperformed the reconstructed representation by 10.25 percentage points for fine phenotypes. Predictive relationships among markers were context-specific. Most targets were better explained by several markers than by one. Marker selection based on these relationships showed a trade-off between panel size and pairwise coverage. Paired samples and imputation can therefore connect selected marker distributions across panels but should not be treated as substitutes for direct measurement. Cross-panel cytometry should be evaluated with patient-held-out tests matched to the resolution of available ground truth and the intended downstream use.

bioinformatics↗

bioRxiv2026

A broadly conserved phytoplasma α/β-hydrolase effector, SGP-7, is a catalytically active esterase that hydrolyses strigolactone analogues and alters shoot architecture

Phytoplasmas are obligate, phloem-limited bacterial pathogens that reprogram host development through secreted effector proteins. The effectors characterized to date, including SAP11, SAP54/PHYL1, SAP05 and SWP1, act principally by binding and destabilizing host transcription factors. Although /{beta}-hydrolase-fold phytoplasma proteins with catalytic activity toward lipid substrates have recently been described, no phytoplasma effector has been shown to possess enzymatic activity toward a plant hormone. The effector RY378 from rice yellow dwarf (RYD) phytoplasma induces excessive tillering and dwarfing in rice and alters strigolactone- and auxin-responsive gene expression; its predicted /{beta}-hydrolase domain was proposed to mediate these effects, but the protein was never expressed, purified or biochemically characterized, leaving the mechanism of this effector class unresolved. From the closed genome of 'Ca. P. sacchari' isolate SCGS, associated with sugarcane grassy shoot disease, we identified SGP-7, an orthologue of RY378 that is conserved across at least seven 16Sr phytoplasma groups. SGP-7 adopts a canonical /{beta}-hydrolase fold with a Ser116-Asp229-His261 catalytic triad, and its predicted substrate pocket is comparable in volume to that of the Arabidopsis strigolactone receptor AtD14. Recombinant SGP-7 is a bona fide esterase with a clear preference for short-chain acyl esters, and hydrolyses both the fluorogenic strigolactone probe Yoshimulactone Green (apparent Km 3.55 uM; kcat 9.38 x 10^-3 s^-1) and the strigolactone analogue rac-GR24. Both activities are abolished by substitution of the catalytic serine (SGP-7S116A). Transient expression of SGP-7 in Nicotiana benthamiana reduced plant height by 46%, increased axillary bud outgrowth approximately fourfold, and lowered transcript levels of the strigolactone-responsive marker NbBRC1, reproducing in a dicot host the architectural phenotype reported for RY378 in rice. Together, these results define the biochemical function of a conserved phytoplasma effector family and identify strigolactone-like molecules as direct enzymatic targets of a bacterial plant pathogen.

microbiology↗

bioRxiv2026

HuMMANet: A Harmonized Cross-Study Resource for Integrative Analysis of Human Gut Microbiome Metabolome Associations

Deciphering gut microbiome to host metabolome interaction is critical for understanding how microbial communities generate bioactive signals that shape host physiology and disease. Progress, however, has been hindered by inconsistent metabolite annotations, poor interoperability across studies, and the absence of integrated resources placing microbiome-derived metabolites within their functional, microbial, physiological, and clinical context. Here we present HuMMANet (Human Microbiome Metabolome Annotation Network), a harmonized resource integrating 46 paired gut microbiome metabolome studies (59 study-units; 14,405 samples; 13 disease categories plus a healthy/control reference category) with a scalable metabolite-harmonization framework. HuMMANet resolves heterogeneous annotations through a multi-stage workflow spanning RefMet, HMDB, PubChem, Metabolomics Workbench, SMPDB, MiMeDB 2.0, GNPS/microbeMASST, DrugBank, and DrugCentral, yielding a reference atlas of 54,914 unique metabolites, annotated with standardized chemical identifiers, biochemical pathways, microbial producer associations, physiological distributions, disease links, and structural relationships to approved therapeutics, a unified reference framework for microbiome metabolome research. Applying HuMMANet to a multi-cohort integration of adult serum and fecal metabolomes, we identified 519 serum and 322 fecal metabolites reproducibly associated with gut microbial community composition (PERMANOVA, P < 0.05 in at least 50% of studies in which detected), enriched for specific biomolecular classes and pathways. Cross-referencing these against Health Associated Core Keystone (HACK) taxa revealed 58 serum and 25 fecal metabolites (HACK positive) whose taxon-level associations tracked positively with the taxon specific HACK indices. These reproducible metabolomic signatures of microbiome health included indole3propionic acid, a gut barrier-protective microbial tryptophan metabolite, and 3phenylpropionate. Drug similarity annotation within HuMMANet linked 16 of this serum and 13 fecal HACK positive metabolites to therapeutics used in neurological, inflammatory, and vascular disease. Conversely, 38 serum and 65 fecal metabolites, including imidazole propionate and long-chain acylcarnitines such as ACar 18:0, showed HACK negative signatures previously associated with dysbiosis-linked disease. GNPS/microbeMASST and MiMeDB 2.0 annotations further traced subsets of these metabolites to putative bacterial producers. HuMMANet thus provides a standardized framework for reproducible microbiome metabolome integration, enabling cross study discovery and translational prioritization of conserved microbiome derived metabolic signatures across human populations and disease states.

bioinformatics↗

bioRxiv2026

Sertraline and Carfilzomib Synergize to Target T-cell Malignancies with Serine/Glycine synthesis activity via Cholesterol Dysregulation, Cellular Stress and Immune Modulation

BackgroundT-cell acute lymphoblastic leukemia (T-ALL) and peripheral T-cell lymphoma (PTCL) are aggressive hematological malignancies requiring novel therapeutic strategies. The majority of T-ALL and PTCL tumors display metabolic activation and addiction to endogenous serine/glycine synthesis (SSP), providing opportunities for targeted therapy with the clinically used antidepressant sertraline, inhibiting SSP enzymes SHMT1/2. However, sertraline monotherapy only induces cell cycle arrest and has limited efficacy in suppressing disease progression in vivo. MethodsDrug synergy of sertraline combined with clinically used proteasome inhibitors carfilzomib and bortezomib was evaluated. Drug effects on cell cycle, proliferation and apoptosis were assessed in T-ALL, PTCL and healthy blood cells using flow cytometry assays. Proteomic, lipidomic and metabolic analyses on drug treated T-ALL cells were performed to elucidate the molecular mechanisms underlying drug synergy, followed by validation of changes of interest, metabolic rescues and shRNA-knockdown of SSP enzymes in T-ALL cells. In vivo therapeutic efficacy and immune remodelling were evaluated in an immunocompetent MYCN-overexpressing PTCL mouse model. ResultsSertraline acted synergistically with clinically used proteasome inhibitor carfilzomib to induce cell cycle arrest and apoptosis in T-ALL and PTCL cells with SSP activity, with minimal effects on SSP-inactive T-ALL cells or healthy blood cells. Adding carfilzomib also enhanced the therapeutic efficacy of sertraline in an aggressive MYCN PTCL model. Sertraline rewired cell metabolism towards increased cholesterol uptake and biosynthesis in SSP-active T-ALL cells, and this effect was not obtained by other means of SSP inhibition. In contrast to sertraline, carfilzomib promoted cholesterol efflux. Moreover, carfilzomib reduced total lipid levels, further restricting nutrients in sertraline - carfilzomib treated cells. Additionally, the drug combination impaired mitochondrial respiration and elevated reactive oxygen species (ROS) levels and DNA damage in SSP-active tumor cells, which was rescued by citrate supplementation. Interestingly, these metabolic changes were associated with microenvironmental changes in our mouse model, where the drug combination elevated natural killer T-cells, neutrophils and eosinophils. ConclusionsOur study identifies synergy of sertraline - carfilzomib combination treatment mediated through metabolic impairment and is associated with remodelling of the immune microenvironment. This invites for further clinical investigation of this drug combination as a therapeutic strategy for SSP-active T-cell malignancies.

cancer biology↗

bioRxiv2026

Solving High-Dimensional Population Balance Equations via Dynamics-Preserving Autoencoders

High-dimensional population balance equations (PBEs) provide a natural framework for modeling heterogeneous cell populations, but their direct numerical solution becomes computationally prohibitive when the internal state space contains many molecular variables. We propose a hybrid mechanistic-machine learning framework for reducing and simulating PBEs defined over high-dimensional intracellular coordinates. The cell population is described by a number density n(x, t), where x [isin] [R]N represents gene and protein states associated with macrophage activation. A dynamics-preserving autoencoder maps this state space to a low-dimensional latent coordinate z [isin] [R]d, with d << N, while retaining key qualitative features of the underlying gene regulatory network, including attractor structure and multistability. Mechanistic information from the original regulatory dynamics is used to construct interpretable drift and diffusion terms for the reduced latent-space PBE. The reduced PBE is solved using a stochastic Lagrangian particle representation, in which particles evolve according to stochastic differential equations (SDEs) corresponding to the latent drift and diffusion fields. The resulting latent-space solution is subsequently decoded and propagated back into the original state space to recover physically interpretable cellular dynamics. We demonstrate the framework on macrophage polarization under cytokine-dependent regulation, including gene knockout perturbations. Overall, the proposed framework provides a computationally tractable and mechanistically interpretable route for integrating single-cell genomic data with population balance models of cell-state dynamics.

systems biology↗

bioRxiv2026

Standardising Cellulose Production From Acetobacter diazotrophicus

Bacterial cellulose (BC) is a biopolymer that comes from natural sources. It has high purity, crystallinity, mechanical strength, and biocompatibility, which makes it suitable for various biomedical and industrial uses. Unlike plant cellulose, BC does not contain lignin or hemicellulose. This results in better material quality and simpler processing. However, producing BC on a large scale is limited by high production costs, expensive culture media, and dependence on a few bacterial strains. It is essential to find cost-effective production methods and alternative microbial sources to expand its commercial use. This study looked at the cellulose-producing ability of Acetobacter diazotrophicus, a safe and relatively unexplored bacterium, under different growth conditions. We compared bacterial growth and cellulose production using Hestrin-Schramm (HS) medium, the standard for BC production, and LB supplemented with glucose (LB+Glucose), which we explored as a more affordable option. We analyzed growth rates, inoculum age, and pH levels to find the best conditions for cellulose production. We observed faster bacterial growth in HS medium, with a doubling time of 3.906 hours, compared to 6.241 hours in LB+Glucose medium. Cellulose production was greatly affected by inoculum age, with successful synthesis from cultures that were agitated for 36 to 40 hours. The highest cellulose yield was at pH 6.0 in HS medium (4.6 mg/mL) and at pH 5.5 in LB+Glucose medium (3.6 mg/mL). FTIR analysis confirmed the presence of characteristic functional groups of bacterial cellulose. These results suggest that Acetobacter diazotrophicus is a promising and cost-effective option for producing bacterial cellulose and highlight the importance of medium composition, inoculum age, and pH for optimizing production.

microbiology↗

bioRxiv2026

A human monoclonal antibody from hybrid immunity exhibits exceptional neutralization breadth against antigenically divergent contemporary Omicron JN.1 lineage variants

Hybrid immunity offers stronger and more durable antibody-mediated protection against symptomatic SARS-CoV-2 infection. In the present study, we report the development of a durable antibody response in an individual with hybrid immunity who also received three doses of the prototype COVID-19 vaccine. Polyclonal plasma antibody obtained from this donor also showed extraordinary neutralization breadth against contemporary Omicron variants. One of the functional monoclonal antibodies (ATHS-C30) isolated from this individual, representing the IGHV4-30 lineage-specific B cell with strong binding affinity to JN.1 spike protein, showed extraordinary neutralization breadth, including variants of Omicron lineages that emerged beyond JN.1, such as KP.2, KP.3.1.1, KP.3.2, KP.3.3, LB.1 and XEC. ATHS-C30 was found to bind RBD with high affinity and showed distinct epitope specificity to the other neutralizing mAbs isolated from the same donor through the epitope binning assay. Molecular modelling of the CDHR3 sequence using existing structures indicated that ATHSC-30 belongs to the class 4 antibody, a feature that contributes to breadth, while epitope conservation analysis indicated that the majority of RBD-interacting residues of ATHSC-30 are evolutionarily conserved. Taken together, our study indicate that ATHS-C30 forms the basis of development of a robust and broadly neutralizing antibody response in this individual with hybrid immunity, which overcomes the antigenic variation by targeting highly conserved and cryptic epitopes in destabilizing the spike structure. ImportanceSARS-CoV-2 continues to pose a significant public health threat, particularly to immunocompromised individuals and older adults with underlying comorbidities. Hybrid immunity to SARS-CoV-2 in vaccinated individuals leads to the development of B cells that are qualitatively superior to those that are expected to develop in only vaccinated individuals. In the present study, we found that among individuals with hybrid immunity who developed robust, durable antigen-specific antibody responses, one developed antibody response capable of broadly cross-neutralising contemporary Omicron variants. This was correlated with development of antigen-specific B cell lineage, such as IGHV4-30, that produced antibodies with potent and extraordinary neutralisation breadth against contemporary Omicron lineages, such as KP.2, KP.3.1.1, KP.3.2, KP.3.3, LB.1 and XEC. This is believed to be due to heterologous antigen exposures driving the development of an antigen-specific B cell repertoire that, in turn, facilitates immune imprinting capable of overcoming the ineffectiveness of antibodies to effectively neutralize newly emerging Omicron variants.

immunology↗

bioRxiv2026

Beyond Bisulfite Sequencing: Resolving 5-hmC with Nanopore Sequencing Unmasks the True-5mC Methylation Entropy Landscape

DNA methylation dynamically regulates cellular function and phenotype. At the tissue level, stochasticity in methylation patterns, as measured by methylation entropy, drives plasticity, development, cancer, and aging. Modulation of methylation patterns is facilitated by erasure of 5-methylcytosine (5mC) via the oxidized intermediate 5-hydroxymethylcytosine (5hmC). Bisulfite sequencing cannot distinguish the two modifications, labeling them both as 5-mC. We quantitatively analyze the effect of this historical conflation on the genome-wide distribution of methylation levels and methylation entropy. Using nanopore sequencing with direct 5mC and 5hmC calling, we compare True-mC to bisulfite-like analysis in two model systems, kidney cancer and the mouse medial prefrontal cortex. We show that bisulfite sequencing introduces systematic, tissue-specific shifts in methylation distribution that affect the mechanistic interpretation of the underlying biology. The distortion scaled with endogenous 5hmC content: substantial in brain, where over half of the entropy-associated gene ontology terms recovered under bisulfite-like analysis were absent under True-mC, and minimal in the low-5hmC kidney cancer sample, which delimits the regime in which bisulfite-derived entropy remains interpretable. Together, these findings establish that True-5mC-based methylation entropy redefines the physical mapping of certain epigenomes, demonstrating that in some contexts, what has previously been interpreted as stochastic maintenance failure is frequently the structured signature of distinct and mechanistically interpretable cytosine biochemistry.

bioinformatics↗

bioRxiv2026

The way less obvious: PIEZO1 supports apoptotic cell extrusion by optimizing tissue mechanical tension for homeostasis.

Apical cell extrusion is a mechanical process that allows epithelia to eliminate apoptotic cells and prevent inflammation. Mechanosensitive ion channels are often invoked for their capacity to mediate rapid mechanical responses in dynamic morphogenetic processes. Here we report an unexpected strategy for PIEZO1 to support apoptotic extrusion. PIEZO1 inhibition blocks extrusion in cultured cells and zebrafish larvae. However, although PIEZO1 mediates calcium signals during the extrusion process, we show that extrusion is instead antagonized by increase in the preexisting mechanical tension of the epithelium when PIEZO1 is disrupted. Correcting enhanced pre-stress in PIEZO1-disrupted epithelia is sufficient to rescue apoptotic extrusion, even though it does not restore dynamic calcium signals. PIEZO1 supports mechanical homeostasis through a calcium/calcineurin-dependent pathway that protects MYPT1/myosin phosphatase from degradation to limit Myosin II activation. Therefore, PIEZO1 support the morphogenetic process of apoptotic extrusion through mechanical homeostasis.

cell biology↗

bioRxiv2026

Co-delivered PD-L1 rescues the protective efficacy mediated by an AAV-expressed HIV-1 bNAb

Adeno-associated virus (AAV)-delivered anti-HIV-1 broadly neutralizing antibodies (bNAbs) could prevent and treat HIV-1 infection but are limited by host immune responses, specifically anti-drug antibodies (ADA). We tested whether PD-L1-mediated immune shielding could improve the consistency of AAV-delivered bNAb expression from muscle tissue in rhesus macaques. AAV9.PD-L1 co-delivery with AAV9.3BNC117 reduced the occurrence of ADA and T cell responses and improved the durability of 3BNC117 expression for one year post administration. Importantly, 5 of 6 macaques that received co-delivered AAV9.PD-L1 vectors were protected against ten repeated SHIVAD8-EO challenges. Histopathological and spatial transcriptomic profiling showed that AAV9.PD-L1 co-delivery prevented severe local inflammation, muscle injury, and tertiary lymphoid structure formation at the administration site. Thus, immune shielding could serve as a strategy to prolong transgene expression from muscle-directed AAV-delivered biologics.

immunology↗

bioRxiv2026

Overcoming host immune responses to an AAV-delivered HIV-1 bNAb in rhesus macaques mediated by co-delivery of PD-L1

Adeno-associated virus (AAV)-delivered anti-HIV-1 broadly neutralizing antibodies (bNAbs) have demonstrated promise for preventing and treating HIV-1 infection in preclinical models. However, host immune responses, specifically anti-drug antibodies (ADA), limit sustained bNAb expression. We have previously shown that PD-L1-mediated immune shielding improves the consistency of AAV-delivered bNAb 3BNC117 expression from muscle tissue in rhesus macaques. Here, we test the breadth of this approach with another bNAb, 10-1074. We show that AAV9.PD-L1 co-delivery with AAV9.10-1074 reduced the occurrence of ADA responses and improved the durability of bNAb expression for one year post administration. Notably 12 of 12 macaques that received AAV9.10-1074 vectors were protected against ten repeated SHIVAD8-EO challenges. Histopathological profiling showed that AAV9.PD-L1 co-delivery prevented severe local inflammation and tertiary lymphoid structure formation at the administration site. Thus, immune shielding could serve as a broad strategy to prolong transgene expression from muscle-directed AAV-delivered biologics.

immunology↗

bioRxiv2026

Coincident epithelial signals restrain commensal-specific CD8αβ+ T cells in the intestine

The intestinal epithelium harbors a large population of microbiota-dependent CD8{beta}+ T cells whose antigen specificity and regulation are ill-defined. By identifying MHCIa-restricted TCRs and generating tetramers against the gut commensal Segmented Filamentous Bacteria, we demonstrate that a single commensal species drives a clonally expanded, antigen-specific CD8{beta}+ T cell within the intraepithelial lymphocyte compartment. Mechanistically, the intestinal epithelium coordinates coincident signals governing this population: peptide:MHC-dependent TCR engagement drives pIEL accumulation, while v{beta}6-mediated TGF{beta} activation restraints effector cell differentiation. Perturbation of epithelial cell-mediated TGF{beta} activation diverts commensal-specific CD8+ T cells toward inflammatory differentiation states transcriptionally convergent with those observed in ulcerative colitis. The intestinal epithelium thus functions as a dual-signal organizer of commensal-specific CD8+ T cell responses, coupling differentiation to restraint through spatially coincident molecular cues.

immunology↗

bioRxiv2026

Generative Augmentation Reveals Previously Overlooked Signals in Transcriptomic Datasets

Identifying robust gene expression signatures from transcriptomic studies with small sample sizes remains one of the most persistent challenges in computational biology. Gene expression datasets have thousands of features but only a handful of biological samples. This presents the classic p >> n imbalance, which limits statistical power and makes it difficult to discover reliable biomarkers. In imaging, generative models such as GANs, VAEs, and diffusion models have demonstrated promising applications in data augmentation, but their usefulness for omics data has not been systematically tested. More importantly, no existing framework integrates synthetic data generation, stability-aware signature discovery, and multi-source biological validation into a single pipeline. In this work, we present GeneLift, with the hypothesis that a computational pipeline of generative data augmentation, stability testing, and evaluating biological evidence will aid novel gene-signature discovery in small-cohort transcriptomic studies. We tested this hypothesis across 36 microarray datasets covering five diseases: sepsis, breast cancer, ovarian cancer, tuberculosis, and diabetes. A component-wise testing of GeneLift revealed that Gaussian Mixture Models (GMMs) outperformed deep generative approaches and faithfully reproduced gene-level distributions. By a novel approach of titrating the level of augmentation, we identified biologically meaningful gene candidates that did not appear in the original, underpowered analyses. We also developed BayesScore, a Bayesian posterior probability of gene-disease association computed from PubMed co-occurrence, which both recovers well-characterised disease genes missed by standard differential expression and surfaces candidates whose disease relevance was independently confirmed in subsequent publications, with lead times of up to 18 years between the source dataset and the first disease-specific citation. GeneLift is freely available at tavlab-iiitd/GeneLift. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=103 SRC="FIGDIR/small/720348v1_ufig1.gif" ALT="Figure 1"> View larger version (41K): org.highwire.dtl.DTLVardef@13c8aeeorg.highwire.dtl.DTLVardef@1c5277corg.highwire.dtl.DTLVardef@a35664org.highwire.dtl.DTLVardef@17cdc48_HPS_FORMAT_FIGEXP M_FIG C_FIG

genomics↗

bioRxiv2026

Repetitive extragenic palindrome (REP) elements are local, context-dependent, dual 3'UTR regulators in Escherichia coli

Repetitive extragenic palindromes (REPs) are the most abundant repetitive noncoding elements in the E. coli genome. Despite their abundance, the primary function of REPs has remained unclear. At different times, REPs have been proposed to contribute to chromosome organization, mRNA decay regulation, and transcription termination, among other functions. Here, we show that the model REP, REP325, does not measurably compact the chromosome but instead acts as a 3UTR-associated transcription regulator within the yjdMN operon, functioning both as a partially Rho-dependent terminator that limits transcription into the downstream yjdN gene and as an mRNA stabilizer that protects the upstream yjdM transcript from degradation. This dual role in controlling both transcriptional readthrough and susceptibility to decay provides a framework that reconciles several previously conflicting observations about REP function. Our genome-wide RNA-seq analysis further reveals that REPs with more canonical sequence and hairpin structures are more often associated with upstream-biased expression in tandem gene pairs, and that REPs positioned between convergent genes correlate with elevated expression of both genes. The large variance in expression patterns in both gene pair configurations is consistent with context-dependent termination and degradation blocking. Similarly, REPs do not uniformly affect mRNA half-lives. Because REP locations vary between E. coli strains, REPs likely contribute to regulatory diversity by tuning gene expression without altering protein-coding sequences or promoter regions, opening new avenues for modulating gene expression through REP-mediated transcription regulation.

biophysics↗

bioRxiv2026

First haplotype-resolved genome assembly of citral-rich lemongrass Cymbopogon flexuosus var. Krishna

Cymbopogon flexuosus var. Krishna (lemongrass) is an aromatic grass valued for its high citral content, which is widely used in the fragrance, flavor, and pharmaceutical industries. C. flexuosus, a member of the Poaceae family, is a predominantly outcrossing species characterized by a highly heterozygous genome. Despite its economic importance and widespread cultivation, a high-quality reference genome has been lacking. Here, we report the first chromosome-scale genome assembly of lemongrass, generated using PacBio HiFi long-read sequencing combined with Omni-C chromatin conformation capture data. The resulting pseudo-haploid assembly spans approximately 798 Mb, organized into 10 chromosomes, and exhibits a scaffold N50 of 64.35 Mb. The assembly demonstrates high completeness, with 99.8% BUSCO recovery, and comprises [~]37,254 predicted protein-coding genes. In addition, we generated haplotype-resolved assemblies that capture the allelic diversity of this heterozygous genome. The haplotypes have sizes of [~]750 Mb and [~]726 Mb, representing 95-98% of the pseudo-haploid genome, and together they provide phase-resolved information for gene families and biosynthetic pathways. These high-quality assemblies establish a foundational genomic resource for advancing molecular breeding, comparative genomics, and metabolic engineering of lemongrass and related aromatic grasses.

genomics↗

bioRxiv2026

Joint Modeling of Transcriptomic and Morphological Phenotypes for Generative Molecular Design

BackgroundEffectively translating data on complex cellular responses from transcriptomic and morphological measurements into molecular design remains a significant computational challenge. Existing generative methods operate on single modalities and condition on post-treatment measurements without leveraging paired control-treatment dynamics to capture perturbation effects. ResultsWe present Pert2Mol, a framework for multi-modal phenotype-to-structure generation that integrates transcriptomic and morphological features from paired control-treatment experiments. Pert2Mol employs bidirectional cross-attention between control and treatment states to capture perturbation dynamics, conditioning a rectified flow transformer that generates molecular structures along straight-line trajectories. We introduce Student-Teacher Self-Representation (SERE) learning to stabilize training in high-dimensional multi-modal spaces. On the Ginkgo Data Platform (GDP) dataset, Pert2Mol achieves Frechet ChemNet Distance of 4.996 compared to 7.343 for diffusion baselines and 59.114 for transcriptomics-only methods, while maintaining perfect molecular validity and appropriate physicochemical property distributions. The model demonstrates 84.7% scaffold diversity and 12.4 times faster generation than diffusion approaches with deterministic sampling suitable for hypothesis-driven validation. ConclusionsPert2Mol establishes a new paradigm for linking high-content phenotypic screening data with computational hypothesis generation in drug discovery: joint multi-modal perturbation modeling enables more accurate and structurally diverse molecular design than single-modality or diffusion-based approaches. Code and pretrained models are available at https://github.com/wangmengbo/Pert2Mol.

bioinformatics↗

bioRxiv2026

Generating Joint Transcriptomic and Morphological Responses to Drug Perturbations via Rectified Flow

MotivationPredicting cellular responses to drug perturbations requires capturing complex dependencies between transcriptomic and morphological changes. Existing approaches model these modalities in isolation, missing critical molecular-phenotypic relationships that occur simultaneously during drug treatment. No current method jointly predicts gene expression profiles and cellular morphology from chemical perturbations. ResultsWe introduce PertFlow, a unified computational frame-work that simultaneously predicts treatment gene expression (bulk RNA-seq) and generates cellular morphology (Cell Painting images) from control cellular states, conditioned on drug metadata. Evaluated on paired RNA-seq and imaging data from 3 cell lines and 40 compounds (17,242 samples), PertFlow achieves Pearson correlation of 0.780{+/-}0.264 for transcriptomic prediction and FID of 24.06 for morphological generation. Board-certified pathologists rated generated images with median similarity scores of 7.11-7.89/10. The model successfully recovers known drug mechanisms including microtubule disruption, DNA damage, and MAPK pathway inhibition, with gene enrichment analysis confirming activation of expected biological pathways (EMT, p53, apoptosis). AvailabilityCode and pretrained models will be available at https://github.com/wangmengbo/PertFlow.

bioinformatics↗