Biology subjects

Prasad, A.

Publications and source records attributed to Prasad, A..

At least 19 recordsLinked to original sources

bioRxiv2026

Skin and Gut Microbiome Features Associated with Resistance to Corynebacterium bovis-Associated Disease in Nude Mice (Mus musculus)

Corynebacterium bovis is an important opportunistic pathogen of immunodeficient mice and the etiologic agent of Corynebacterium-associated hyperkeratosis (CAH). Although disease severity varies, specific vendor-derived microbiomes have been shown to protect against CAH. Preinoculation with nonpathogenic Corynebacterium amycolatum prior to C. bovis infection has been demonstrated to limit disease severity. To define community features associated with protection, axenic outbred athymic nude mice stocks (A, B, and C) were reassociated with donor microbiomes from four vendor sources (A1, A2, B, and C) and topically challenged with C. bovis. C. amycolatum was added to the A1 microbiome in a separate group. Skin (Stock A) and fecal (Stocks A, B, and C) microbiomes were evaluated at 21 days post-inoculation via shotgun metagenomic sequencing. The A2 microbiome, previously associated with resistance to clinical disease and minimal skin pathology, exhibited greater cutaneous microbial evenness after challenge and significantly lower relative abundance of C. bovis than all other microbiome groups. Addition of C. amycolatum to the A1 microbiome did not fully confer disease protection and relative abundance was low, suggesting that sustained colonization by this organism was insufficient to explain the protective phenotype seen with the A2 microbiome. C. kroppenstedtii was detected in all A2 skin samples and was absent from all other groups. Several anaerobic taxa, including Duncaniella dubosii, D. muris, Bacteroides caecimuris, and Muribaculum gordoncarteri, were uniquely detected or enriched in the A2-associated microbiome, whereas Mammaliicoccus lentus and Staphylococcus nepalensis were absent from A2 but present in all nonprotective groups. Gut alpha diversity did not differ significantly among microbiomes, although several taxa, including segmented filamentous bacteria, were enriched in A2 feces. These findings associate resistance to CAH with preservation of cutaneous community structure, suppression of C. bovis prominence, and distinct microbial taxa. The identified organisms represent candidates for future mechanistic studies of microbiome-mediated colonization resistance.

zoology↗

bioRxiv2026

Programmable Self-Assembly of RNA Nanostructures with >100 Unique Components

Sophisticated biomolecular functions often arise from large, precisely organized architectures, motivating efforts to construct increasingly complex structures through programmed nucleic acid self-assembly. Although RNA offers a richer repertoire of structural motifs and biological functions than DNA, RNA nanostructures constructed to date have remained substantially less complex and less scalable than their DNA counterparts, most notably DNA origami and DNA bricks, which rely on large libraries of synthetic single-stranded (ss) DNA strands. Directly adapting these strategies to RNA, however, faces two major barriers: (i) the high cost of producing large libraries of distinct synthetic ssRNA strands, and (ii) the limited stability of ssRNA under conditions commonly used for assembling multicomponent nucleic acid nanostructures. Here we present the double-stranded RNA (dsRNA) bricks approach, which addresses both barriers by adopting principles inspired by natural RNA systems: (i) many distinct RNA components ("bricks") are encoded within a single precursor transcript and released by enzymatic processing, (ii) each brick's predominantly double-stranded nature enhances stability. The resulting dsRNA bricks self-assemble through programmable branched kissing-loop interactions. Using this approach, we constructed complex two- and three-dimensional RNA nanostructures with more than 100 distinct components, representing, to our knowledge, the largest and most compositionally complex RNA nanoarchitectures reported to date. Overall, the dsRNA bricks approach establishes a scalable and robust framework for constructing complex RNA nanostructures with compositional and architectural sophistication approaching that of DNA-based systems, thereby opening new opportunities for programmable RNA materials and RNA-based devices.

synthetic biology↗

bioRxiv2026

Pathogenesis and natural history of the Bundibugyo species of Orthoebolavirus in nonhuman primates

The current outbreak of Bundibugyo virus (BDBV) in Africa is a global public health concern particularly as there are no licensed medical countermeasures (MCM). Well characterized animal models that accurately replicate human BDBV infection are needed to develop effective MCM. We exposed 21 cynomolgus monkeys (CM) to BDBV to examine the progression and natural history of BDBV disease (BVD). BVD was more protracted than reported for Ebola and Sudan infection in CM with a lower lethality rate of 67% consistent with lower human BVD mortality rates. IHC and spatial proteomics identified CD209+, CD68+, and/or HLA-DR+ macrophages and dendritic cells as early targets of BDBV. These infected cells frequently colocalized with fibrin and infiltrating MPO+ neutrophils and S100A9+ myeloid-derived suppressor cells, consistent with the development of an active inflammatory response and early coagulopathy. Transcriptomic and proteomic analyses of the circulating immune response correspondingly reflected a cytokine-driven hyperinflammatory state in CM that succumbed to disease. Surviving animals resolved systemic inflammation by the study endpoint; however, BDBV antigen was identified in immune privileged tissues with lesion-associated inflammation aligning with known post-Ebola sequela in humans. This data should assist in identifying weaknesses in the disease course that can be exploited to develop new MCM.

microbiology↗

bioRxiv2026

A Charge-Encoded Rheostat Permits Helix Nucleation but Limits Propagation in Skp1

Molecular recognition by intrinsically disordered regions (IDRs) is widely thought to involve coupled folding and binding, yet the sequence features that regulate this transition remain underexplored. Here we show that helix 8 (H8), a disordered C-terminal segment of the SCF ubiquitin ligase adaptor Skp1, is intrinsically prevented from forming a stable helix by its own sequence grammar. Using an integrative approach to dissect its conformational dynamics, we find that H8 frequently nucleates helical structure but rarely propagates into a fully formed stable helix, populating instead a shallow metastable basin of helical intermediates. Contrary to conventional models of helix-coil exchange, where nucleation is rate limiting, helix initiation in H8 is readily accessible, while propagation is selectively suppressed by a glutamate-rich acidic patch. This acidic segment acts as a charge-sensitive conformational rheostat that limits helix extension and maintains H8 in a predominantly disordered state. As a result, H8 transiently samples partially helical conformations on the microsecond timescale without committing to a stable fold. We propose that this propagation-limited mechanism preserves conformational flexibility while maintaining recognition competence across a structurally diverse family of F-box binding partners. More broadly, our findings suggest that charged- hydrophobic-charged sequence patterning can encode conditional, context-dependent structure as a general organisational principle in intrinsically disordered proteomes.

biophysics↗

bioRxiv2026

Modulating Inflammation in Post-Traumatic Osteoarthritis using iPSC-derived Anti-inflammatory Macrophages

Post-traumatic osteoarthritis (PTOA) is a common long-term consequence of joint injury and a major cause of chronic pain and disability, yet no disease-modifying therapies are currently available. A central barrier to effective intervention is the persistence of maladaptive synovial inflammation, driven in part by macrophage-mediated signaling that sustains tissue degeneration and pain. Here, we developed a scalable, chemically defined platform to generate human induced pluripotent stem cell (iPSC)-derived anti-inflammatory macrophages (iMac-M2) as an off-the-shelf cell therapy designed to restore joint immune homeostasis after injury. These cells maintained a stable anti-inflammatory phenotype and function under osteoarthritis-relevant inflammatory conditions and suppressed inflammatory and catabolic responses in human joint cell co-culture systems. In a preclinical model of PTOA, intra-articular delivery of iMac-M2 after injury improved functional and structural outcomes while modulating synovial inflammatory and pain-associated transcriptional programs. Treatment was well tolerated, with no evidence of systemic immune activation or ectopic tissue formation. Together, these findings support iPSC-derived macrophage therapy as a clinically translatable immunomodulatory strategy to interrupt early inflammatory drivers of PTOA and preserve joint health following injury.

cell biology↗

bioRxiv2026

Impact of variability in cell generation times on cell-to-cell variability of protein concentrations

The influence of arbitrary randomness in cell division times on the variability of protein copy numbers within a lineage ensemble has been recently studied, going beyond the contributions of noisy gene expression and partitioning error. However, variability of protein concentrations need separate study, since cell size growth between cell divisions dilute protein concentrations at the same rate as size growth, which also determines mean division times. Here for a model of bursty protein production, we present exact moments (of all orders) of protein concentrations in the cyclo-stationary state, comparing: (i) population and lineage cell ensembles, and (ii) statistics at different cell ages. Two interesting results emerge. While the variance of protein concentration changes with the degree of division time heterogeneity at any cell age, the age-averaged variance is independent of it within lineage ensemble but stays dependent within population ensemble. The skewness within population ensemble is higher in younger cells than within lineage ensemble, and this behavior reverses at older ages. Such a feature vanishes for the age-averaged distribution, with population based skewness always dominating over that of lineage. We also show that mother-daughter correlations in generation times, do not add any significant difference to the results.

systems biology↗

bioRxiv2026

Feeder-Free Generation of Lymphatic Endothelial Cells from Human Induced Pluripotent Stem Cells

AbstractThe lymphatic system is essential for maintaining fluid homeostasis, lipid transport and supporting immune function. Despite its central role in health and disease, advancements in understanding human lymphatic vasculature has been constrained, in part because primary human LECs are difficult to access and study in disease-relevant contexts. This study describes an efficient and scalable feeder-free method to differentiate human iPSCs into lymphatic endothelial cells (LECs) that are transcriptionally and phenotypically similar to primary fetal LECs. An iPSC-derived LEC system overcomes a drawback of primary cells by enabling precise genetic perturbations, supporting study of lymphatic diseases of interest in a human context. By grounding our approach in in vivo stages of lymphangiogenisis, we describe a staged protocol that recapitulates the key milestones of lymphatic development. We first adapted a published method to differentiate human iPSCs into venous endothelial cells (VECs) and then initiate transdifferentiation of VECs into LECs. Using immunocytochemistry, qPCR, as well as flow cytometry, we demonstrated expression of lymphatic-specific markers in the differentiated population. We further characterized our induced VECs (iVECs) and LECs (iLECs) through bulk RNA sequencing analysis and compared the populations to pseudobulk VEC and LEC transcriptomic datasets generated from human fetal heart endothelia at 12, 13 and 14 weeks of gestation. Through this work, we expanded the repertoire of approaches for accessing LECs, with the goal of accelerating discoveries in lymphatic biology and therapeutics. Abstract summary image O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=171 SRC="FIGDIR/small/712968v1_ufig1.gif" ALT="Figure 1"> View larger version (15K): org.highwire.dtl.DTLVardef@1a9a406org.highwire.dtl.DTLVardef@4faec6org.highwire.dtl.DTLVardef@15b4e73org.highwire.dtl.DTLVardef@17b9c36_HPS_FORMAT_FIGEXP M_FIG C_FIG

developmental biology↗

bioRxiv2026

The pyruvate branch point controls lymphoid cancer cell dissemination

Cancer cell dissemination critically determines clinical prognosis, yet metabolic dependencies and corresponding therapeutic targets during spread of lymphoid malignancies remain poorly understood. Here we show that the pyruvate branch point operates as a metabolic checkpoint for lymphoid cancer cell migration and disease dissemination through mitochondrial ROS (mROS)/HIF-1a signaling. Isolation of highly migratory mROShi cells led us to identify selective metabolic requirements of malignant lymphocyte migration and disease dissemination. Highly migratory cells show a reprogrammed metabolic profile characterized by increased glucose uptake and reduced glucose-carbon entry into the TCA cycle. Reprogramming of the TCA cycle with downregulation of citrate synthase provide the mechanistic basis for decreased pyruvate oxidation leading to increased migration and disease dissemination through mROS/HIF-1a signaling. Our findings connect central carbon metabolism and migratory capacity of lymphoid cancer cells and identify the pyruvate branch point as a metabolic switch and potential therapeutic target in lymphoid cancer cell dissemination.

cancer biology↗

bioRxiv2026

Glydentify: An explainable deep learning platform for glycosyltransferase donor substrate prediction

Glycosyltransferases (GTs) are a large family of enzymes that catalyze glycosidic linkages formation between chemically diverse donor and acceptor molecules to regulate diverse cellular processes across all domains of life. Despite their importance, the activated sugar donors (donor substrates) used by most GTs remain unidentified, limiting our understanding of GT functions. To address this challenge, we developed Glydentify, a deep learning framework that predicts donor usage across GT-A and GT-B fold glycosyltransferases. Trained on large-scale UniProt annotations, Glydentify integrates protein sequence embeddings learned from protein language models with chemical features derived from molecular encoders trained on extensive chemical datasets. The resulting models achieve high predictive performance, with precision-recall AUCs (PR-AUC) of 0.86 for GT-A and 0.91 for GT-B, surpassing general enzyme-substrate predictors while requiring minimal manual curation. We employed Glydentify to predict the donor specificity of uncharacterized plant GTs and experimentally tested the predictions using in vitro biochemical assays. Furthermore, we demonstrate that the model utilizes a combination of evolutionary, structural, and biochemical features to predict donor specificity through residue attention score analysis. Together, these results establish Glydentify as a robust, explainable framework for decoding donor-glycosyltransferase relationships and highlight its potential as a broadly applicable framework for modeling enzyme classes that act on chemically diverse substrates.

bioinformatics↗

bioRxiv2026

Morphological parameters can capture emergent properties of dynamic disordered cytoskeletal networks

The actin cytoskeleton is an inherently disordered active system. the actomyosin cortex and reconstituted actomyosin systems are globally disordered, yet undergo transitions between distinct disordered states as parameters like motor and crosslinker concentration and filament length and rigidity change. In cells these changes are related to genetic mutations or differences in cell state and dictate fundamental biological processes. However, we dont have well established methods to detect and classify differences in disordered polymer networks. Image-based morphology techniques provide a non-invasive, high-throughput method of extracting information about a system. In this work we simulate biopolymer networks under varying conditions and develop and use morphological descriptors to construct trajectories in morphospace. Using statistical analysis we find that morphological descriptors are able to distinguish between different trajectories of the system, including differences not apparent to the eye. However, no single descriptor alone is able to capture all the differences in the simulated trajectories. Nematic order parameters typically perform the worst for our simulations while curvature and texture descriptors can collectively distinguish between dynamic trajectories. This work helps develop quantification of cytoskeleton dynamics for classification and data-driven modeling.

biophysics↗

bioRxiv2026

Quantitative modeling reveals sources of variability in transcriptional activation assays

Reporter cell assays, such as those used to detect estrogenic chemicals, can detect target chemicals at low concentrations and can be used to analyze chemical mixtures without a priori knowledge of the mixture components. However, the outputs of these assays are affected by biological variability, which complicates their interpretation. Here, we describe and demonstrate a workflow that is useful for determining potential sources of biological variability and optimizing the performance of cell-based assays. The workflow involves developing an appropriate mathematical model for a transcriptional activation assay, calibrating it with experimental data, and conducting sensitivity analysis to characterize individual components of the genetic circuit based on their effect on the reporter signal output. This workflow was tested using an estrogen receptor transcriptional activation assay. For this circuit, our analysis predicts that controlling estrogen response element number, promoter strength, and reporter signal degradation rates minimizes reporter output variability. We show that careful model development, calibration, and analysis can offer biologically relevant insights to minimize the variability of cell-based assays and improve genetic circuits for increased sensitivity and dynamic range.

synthetic biology↗

bioRxiv2026

DNA-templated Chiral Metamaterial Array as Information Bits

The growth of digital information demands physically secure information bits that combine intrinsic randomness with multi-layered optical readout. Digital metamaterials with physical unclonable function characteristics are promising, but nearly all examples operate at microwave or terahertz frequencies. Extending digital metamaterials to the visible range requires a physical property that allows binary (0/1) encoding via nanoscale geometry and is orthogonal to intensity-or color-based imaging. Chiral plasmonic metamaterials satisfy these criteria perfectly: their broken mirror symmetry yields chirality polarity in the visible spectrum whose sign and magnitude directly encode bit values ("0", spin-up; "1", spin-down), while remaining invisible under linear polarization. Here, we realize visible-range digital metamaterials by programming self-assembled DNA origami templates with asymmetrically placed gold nanorods to create discrete 3D chiral metamolecules. Using on-surface DNA origami assembly and the Silica Microsphere-Assisted Patterning by Liquid Elimination (SiMPLE) method, we fabricate large-scale bit arrays on optical active glass substrate in solution with [~]1.33 m lattice spacing, [~]86% site occupancy, and [~]12-month stability after silicification. These bottom-up fabricated digital metamaterial array exhibits two independent security layers: (1) a macroscopic spatial pattern only visible by dark-field microscopy, and (2) hidden binary information stored in the single-particle chiroptical response, read out by position-resolved circular dichroism spectroscopy. Quantitative analysis confirms reliable bit encoding and high optical randomness arising from slight structural variations. By leveraging the polarity of plasmonic chirality to translate molecular-scale handedness into robust visible-range digital signals, this work establishes a scalable nanophotonic platform for secure optical information storage, authentication, and encryption.

bioengineering↗

bioRxiv2026

Dysregulated TGFb-ERK Signaling Drives Aberrant Extracellular Matrix Production in Noonan Syndrome-Associated Pulmonary Valve Stenosis

Pulmonary valve stenosis (PVS) is the most common congenital heart defect in Noonan syndrome (NS) and related RASopathies, yet the molecular mechanisms linking pathogenic variants to the valve pathology remain poorly defined. Here, we utilized a human iPSC-based valve differentiation platform to generate the cardiac valve cell lineages--including fibrosa and spongiosa valve interstitial cell (VIC) subtypes. CRISPR-edited iPSCs harboring NS gain-of-function RAS/MAPK and Noonan syndrome with multiple lentigines (NSML) dominant-negative RAS/MAPK variants exhibited early defects in mesodermal and endocardial specification in all genotypes. Additionally, NS-iPSC endocardial cells exhibited defects in endothelial-to-mesenchymal transition (EndMT) specifically towards fibrosa VICs, which was most pronounced in PTPN11N308D (N308D) cells. Single-cell transcriptomics revealed widespread dysregulation of extracellular matrix (ECM) programs in N308D fibrosa VICs, including increased expression of collagens and proteoglycans, as well as dysregulation of multiple genes involved in ECM remodeling. We also detected activation of RAS-MAPK, TGF{beta}, and fibrosis-associated pathways in our transcriptional dataset. Mass spectrometry-based phosphoproteomics confirmed coordinated increases in ERK, PKC, and stress-related kinases, as well as enhanced activity of the TGF{beta} receptor. Functionally, N308D fibrosa VICs exhibited exaggerated upregulation of ECM genes in the presence of TGF{beta}2 ligand, suggesting that these cells are hypersensitive to TGF{beta} stimulation. Furthermore, we demonstrated that this pathological ECM-program occurs independently of BAMBI, a negative regulator of TGF{beta} signaling that was found to be decreased in N308D fibrosa VICs. Lastly, we performed histopathological analyses of stenotic pulmonary valves from two NS infants, which demonstrated marked overproduction and disorganization of ECM, mirroring the findings from our iPSC-based disease model. Together, our data reveal a central mechanism where NS-associated alleles sensitize fibrosa VICs to TGF{beta}, which leads to aberrant downstream signaling and drives the pathological ECM program in NS-associated PVS.

cell biology↗

bioRxiv2025

Host and microbial factors influence bacterial colonization of the honey bee gut

The guts of many animals are colonized by host-specific microbes, yet the extent to which host filtering (host-derived constraints) shapes microbial colonization and host specificity remains poorly understood. Here, we used gnotobiotic honey bees (Apis mellifera) as a model system to systematically assess the colonization potential of a phylogenetically and ecologically diverse panel of 56 bacterial strains, spanning native symbionts, opportunistic bee-associated taxa, gut microbes from other bee species, and non-bee environmental isolates. Bacterial load and colonization frequency were quantified by strain-specific qPCR seven days post-inoculation, in monocolonization and in the presence of a synthetic community composed of native honeybee core bacteria. Bacterial load was highest for native strains and declined with increasing phylogenetic distance from native symbionts. Co-colonization with the synthetic community reduces load across all groups, but native strains were least affected. Across strains, completeness of KEGG metabolic pathways correlated with bacterial load in some ecological groups; however, metabolic capacity alone did not fully explain colonization patterns, either in monocolonization or under competitive conditions. A key finding was that in vitro sensitivity to antimicrobial peptide (AMPs; apidaecin, abaecin, defensins, hymenoptaecin) varied widely among strains and was highest in closely related bee-associated bacteria. Notably, even highly successful colonizers such as Gilliamella and Snodgrassella were AMP-sensitive. AMP sensitivity showed a negative correlation with bacterial load, but not with the frequency of host colonization. These findings suggest that AMPs modulate symbiont abundance rather than acting as strict barriers to colonization. Overall, our results reveal that host filtering in the bee gut is multifaceted, integrating immune-mediated barriers, microbial traits, and competitive interactions.

microbiology↗

bioRxiv2025

Gut microbiota variation across sympatric stingless bee species and honey bees in the Neotropics

Stingless bees (Meliponini) are ecologically and culturally important pollinators with a long tradition of human management in the Neotropics. Yet, little is known about how their gut microbiota vary across geographic regions or whether microbial exchange occurs with managed honey bees (Apis mellifera), which are often kept in close proximity. Using full-length 16S rRNA gene sequencing of individual bees sampled from 167 colonies, we characterized gut microbial community structure through a hierarchical, taxonomic and phylogenetic comparative framework, contrasting the microbiota of Melipona quadrifasciata and Melipona mondury with that of Apis mellifera across their shared geographic range in Brazil. The core microbiota of Melipona was dominated by Lactobacillus, Bifidobacterium, Apilactobacillus, Bombella, and Floricoccus, and showed inverse variation in relative abundance with lower-prevalence bacterial taxa. Although the core microbiota of the two stingless bee species overlapped only partially with that of Apis mellifera, they exhibited comparable alpha-diversity and beta-diversity dispersion, indicating broadly similar community assembly processes and dynamics. Nevertheless, we found that 6% of all amplicon sequence variants (ASVs) were shared between hosts, encompassing nearly all canonical honey bee "core" symbionts, indicating frequent spillover. Remarkably, several ASVs of Snodgrassella, a genus typically rare in stingless bees, reached high abundance in several M. quadrifasciata individuals and formed a deeply divergent clade ([~]96% 16S rRNA gene identity to S. alvi). These patterns are consistent with the hypothesis that human-mediated management practices, such as mixed apiaries and artificial feeding, create opportunities for microbial exchange between native and non-native bees. Together, our findings indicate that stingless bee gut microbiomes are compositionally stable yet ecologically permeable, shaped by both long-term host specificity and recent anthropogenic contact.

ecology↗

bioRxiv2025

Priority effects determine community composition at the strain level in the honeybee gut microbiota

Gut microbial communities often differ at the strain level among individual hosts, but the mechanisms driving this variation remain poorly understood. One potential factor is priority effects, a process in which differences in the timing and order of microbial colonization influence subsequent community assembly ("first come, first served" dynamics). We hypothesize that such priority effects operate at the strain level within species, where closely related bacteria exhibit niche overlap, and that these dynamics can lead to community divergence even under similar environmental conditions. We tested these predictions, using the gut microbiota of honeybees, which harbor conserved microbial communities that differ in strain composition among individual bees. We sequentially colonized microbiota-depleted honeybees with two distinct microbial communities composed of the same twelve core microbiota species but different strains, ensuring that individuals shared species-level composition but differed at the strain level. We found that firstcomer strains consistently dominated the resulting communities, suggesting strong priority effects. Dropout experiments in which the firstcomer strain of a species was removed led to only partial increases in the colonization success of the conspecific latecomer, suggesting that both intra- and inter-species interactions contribute to priority effects. Our findings highlight the significant role of priority effects in strain-level community assembly and reveal their influence in shaping the specialized gut microbiota of honeybees, with important implications for the development of probiotic strategies in beekeeping. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=134 SRC="FIGDIR/small/689826v1_ufig1.gif" ALT="Figure 1"> View larger version (32K): org.highwire.dtl.DTLVardef@b0930eorg.highwire.dtl.DTLVardef@8687c5org.highwire.dtl.DTLVardef@3ba838org.highwire.dtl.DTLVardef@a10c3e_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

bioRxiv2025

Matrix Stiffness Dictates Doxorubicin-Induced Apoptosis by Modulating Cell-Cycle State in HeLa Cells

Drug resistance remains a major challenge in cancer treatment by contributing to recurrence and metastasis. Fractional killing, in which only a subset of cells undergo apoptosis after drug exposure, is a key contributor to this resistance and is influenced by genetic and nongenetic heterogeneity within the tumor microenvironment. Solid tumors display substantial variation in extracellular matrix stiffness, providing evidence that the mechanical context of cancer and stromal cells may play an important role in therapeutic response. Here, we investigated how substrate stiffness affects the dynamics of apoptosis and the mechanisms behind differences in the cell death response to doxorubicin (DOX). HeLa cells cultured on stiffer substrates exhibited enhanced caspase-3/7 activation and increased apoptotic cell death, whereas cells on soft substrates showed markedly reduced apoptotic signaling and improved survival. Although substrate stiffness altered cytoskeletal organization, pharmacological disruption of actin polymerization or actomyosin contractility did not influence nuclear DOX accumulation, indicating that cytoskeletal mechanics were not the primary factor in the stiffness-dependent sensitivity. Instead, flow cytometry revealed that substrate stiffness modulates cell-cycle distribution, with soft substrates enriched in the G1 population and a reduced fraction of cells in the DOX-sensitive S phase. Synchronizing cells at the G1/S phase boundary eliminated stiffness-dependent differences in apoptotic activation, demonstrating that cell-cycle state is a dominant driver of stiffness-mediated fractional killing. These findings highlight a mechanistic link between extracellular matrix mechanics and chemotherapeutic response by suggesting that microenvironment-regulated cell-cycle dynamics contribute to drug resistance in mechanically heterogeneous tumors.

biophysics↗

bioRxiv2025

Metal speciation and bioavailability in microbial growth media

Microbial growth in both natural environments and artificial media is strongly influenced by metal speciation, which can be quantitatively modeled for a given chemical composition. Despite its importance, metal speciation is rarely incorporated into the design of microbial growth experiments, often leading to misinterpretations of metal bioavailability and toxicity. In this study, we revisit two historical microbial investigations: one that drew inaccurate conclusions due to the absence of speciation calculations, and another that relied on flawed assumptions about metal speciation. Through targeted recalculations, we demonstrate how these oversights impacted the interpretation of metal-microbe interactions including the applicability of the free ion activity model (FIAM). Additionally, we perform metal speciation analyses for a bacterial growth medium to illustrate how speciation can clarify distinctions between stimulatory and non-essential metals. Further simulations were conducted for six DSMZ-listed microbial media and six chemical variants of a representative medium, using estimated stability constants where experimental data were unavailable. Collectively, this work underscores the value of integrating metal speciation calculations into microbial research to improve the accuracy of conclusions regarding metal bioavailability and toxicity.

microbiology↗