Biology subjects

Nayak, S.

Publications and source records attributed to Nayak, S..

At least 19 recordsLinked to original sources

bioRxiv2026

White matter cognition mapping in pediatric cancer survivors: a two-cohort NODDI-Bingham study

Childhood cancer survivors (CS) treated with chemotherapy frequently experience long-term cognitive impairments, commonly referred to as CRCI. Whether these deficits reflect disrupted white matter microstructure, altered relationships between microstructure and cognition, or both remains unclear. Here, we applied the NODDI-Bingham model, which quantifies neurite density (NDI), isotropic free water (ISO), and orientation dispersion along primary (ODIp), secondary (ODIs), and total (ODIt) fiber axes, to characterize biophysically specific white matter microstructure in CS and examine its relationship to cognition. Twenty-one pediatric cancer survivors and 21 age-matched healthy controls (HC) underwent multi-shell diffusion MRI. Voxel-wise NODDI-Bingham analyses were performed within JHU atlas regions. Group differences were tested by ANCOVA, and associations between microstructure and cognition were examined with the NIH Toolbox Crystallized, Fluid, and Early Childhood composites using group-specific regressions. Confirmatory analyses were performed in an age-matched subsample of the HCP (n = 679). Notably, CS showed reduced NDI in the corona radiata, cerebral peduncles, and corpus callosum, with elevated ODIt and ODIp in the middle cerebellar peduncle, pathways that subserve processing speed and interhemispheric integration, cognitive domains among the most vulnerable in CRCI. Group-specific regressions revealed qualitatively different relationships between microstructure and cognition: HC exhibited mixed positive and negative relationships across four of five metrics (138 clusters spanning approximately 305,000 voxels; peak Cohen's d up to 3.00), whereas CS showed a predominantly uniformly negative pattern (67 clusters across 57,000 voxels), with no positive clusters for ISO, ODIt, ODIp, or ODIs, thus highlighting that reduced dispersion and extracellular free water are linked to better cognitive performance in CS. HCP analyses reproduced the HC pattern across all five metrics at proportionally smaller effect sizes, ruling out sample-size effects. NODDI-Bingham identifies two aspects of chemotherapy-related white matter pathology that standard diffusion metrics cannot resolve. First, pediatric cancer survivors show selective elevation of ODIp and ODIt in the cerebellar peduncles and reduced NDI in the corona radiata and corpus callosum, localizing group-level injury to specific fanning and neurite density signatures. Second, whereas in healthy controls white matter shows mixed positive and negative relationships between microstructure and cognition, survivors retain only negative relationships for ODIp and ODIt and a diminished mixed pattern for NDI, such that in the chemotherapy-exposed brain, only reduced neurite density and increased primary-axis fanning relate to cognitive impairment. These findings implicate a biophysically specific restructuring of the relationships between white matter and cognition as a candidate mechanism for CRCI and support NODDI-Bingham as a targeted biomarker panel for monitoring and intervention trials.

neuroscience↗

bioRxiv2026

A chromosome-scale Plasmodium cynomolgi Berok genome reveals a distinct subtelomeric architecture and a highly diverged primate malaria lineage

Plasmodium cynomolgi is the closest relative of P. vivax and the primary experimental model for relapsing malaria, hypnozoite biology, and blood-stage drug susceptibility. Yet existing reference genomes remain fragmented, leaving structurally complex, AT-rich regions largely unresolved. We generated a chromosome-scale genome assembly for the K4-A7 cloned line of P. cynomolgi Berok by combining Hi-C chromosome conformation capture, Oxford Nanopore long reads, PacBio, and Illumina sequencing. The assembly spans 14 chromosomes plus mitochondrial and apicoplast genomes, with only seven unplaced minor contigs, the fewest for any non-P. falciparum Plasmodium genome, and an N50 of 3.06 Mb. Critically, this hybrid strategy resolved approximately 8 Mb of extremely AT-rich (~20% GC) sequence onto chromosomes 4, 8, and 13, anchoring what were previously unplaced or absent contigs into a continuous chromosomal framework. These subtelomere-like expansions (SLEs) constitute ~26.5% of the chromosomal genome and are enriched for PIR/VIR, STP1, variable surface antigen, and methyltransferase pseudogene families. Despite low gene density, SLE-encoded genes are transcriptionally active and show stage-specific expression across the erythrocytic cycle. Integrated lifecycle transcriptomics across 7,006 genes revealed a ~54-hour erythrocytic cycle with a "just-in-time" transcriptional cascade closely resembling that of P. vivax. Phylogenomic analyses and pairwise amino acid comparisons across more than 2,600 single-copy orthologs show that Berok forms a deeply diverged P. cynomolgi lineage, suggesting a distinct subspecies. This assembly establishes a high-resolution genomic foundation for comparative malaria biology, drug discovery, and the study of subtelomeric architecture, host adaptation, and lineage boundaries in primate Plasmodium.

microbiology↗

bioRxiv2026

The Synthetic Fidelity-Stability Framework (SFSF): A Systematic Multi-Dimensional Benchmark of Synthetic Clinical Laboratory Data Generators

BackgroundSynthetic data generation is increasingly proposed as a strategy to support privacy-preserving data sharing, augmentation of small or restricted biomedical datasets, and benchmarking of artificial intelligence tools in laboratory medicine. However, model selection remains difficult because synthetic data generators differ in fidelity, privacy risk, stability, and generalisability. Existing evaluations have rarely examined performance jointly across conditioning signal strength, synthetic output scale, and train-test generalisation. MethodsWe developed the Synthetic Fidelity-Stability Framework (SFSF), a systematic benchmark of 17 synthetic tabular data generation models using NHANES as a complex biomedical reference dataset. Models included statistical, copula-based, resampling, variational autoencoder, generative adversarial network, and diffusion-based approaches. Synthetic datasets were generated across 11 seed sizes, from 0 to 500 real conditioning observations, and six output scales, from 50 to 5,000 rows, yielding 1,122 synthetic datasets per run. Each dataset was evaluated against the full original dataset, the training subset, and a held-out test subset across five tiers: univariate distributional fidelity, moment agreement, tail behaviour, multivariate dependency structure, and privacy/memorisation risk. Composite rankings and seed-versus-output stability profiles were derived. ResultsUnivariate fidelity was broadly recovered across model classes and was the least discriminating tier. Resampling-based methods ranked highest overall but showed the greatest privacy risk, reflecting proximity to real observations rather than true generative novelty. VAE-family models reproduced moment statistics relatively well but consistently failed on tail and shape fidelity. GAN-family models showed substantial moment-level instability, while VineCopula demonstrated severe multivariate dependency failure. Diffusion-based models, particularly ForestDiffusion, provided the most favourable privacy-utility balance, combining competitive fidelity with the lowest privacy risk and the smallest train-test gap. ConclusionsNo single synthetic data generator dominated across fidelity, stability, and privacy dimensions. The SFSF framework provides a practical, multi-criterion approach for selecting synthetic tabular data generators according to intended clinical laboratory use, balancing statistical realism, dependency preservation, privacy risk, and robustness to seed and output scale.

biochemistry↗

bioRxiv2026

Screening of Potential Vaccine Candidate and Sera Based Diagnostic Markers from N-linked Surface Glycoproteins of Entamoeba histolytica

Pathogenesis inflicted by Entamoeba histolytica causes amoebic diarrhea and liver abscesses and is one of the leading causes of mortality from parasitic disease worldwide. Preventive therapeutics in the form of a vaccine could be highly effective at providing umbrella protection for a vulnerable community. In this study, a group of ten putative hypothetical surface N-linked glycoproteins was examined to assess their potential as vaccine candidates and/or diagnostic markers against amoebic intestinal colitis and liver abscesses. To evaluate the immunogenicity of putative surface glycoproteins, we used Entamoeba histolytica-infected patients sera from Bangladesh and then assessed the titer of antibody these glycoproteins elicited in patients by enzyme-linked immunosorbent assay (ELISA) and immunoblot. Based on this study, eight of ten surface glycoproteins were found immunogenic, as specific antibodies against these glycoproteins were detected in patients sera. Three of the immunogenic glycoproteins showed strong IgG antibody responses in both patients with intestinal amoebiasis and those with liver abscess. On the other hand, the other two glycoproteins showed the presence of specific serum antibodies exclusively in patients with amoebic liver abscesses, not in individuals with amoebic colitis. The remaining two glycoproteins showed more specific sera antibodies against ALA, but the preference was not very distinct. Immunolocalization with a specific antibody against the most immunogenic glycoproteins further confirmed their presence in the cell membrane. This differential immunogenicity of these glycoproteins in the two groups of patients qualifies them to become prospective sera-based diagnostic markers and also has the potential to become vaccine candidates for amoebiasis protection.

immunology↗

bioRxiv2026

Cognitive Control in Pediatric Cancer Survivors: A task-fMRI study

BackgroundChemotherapy-related cognitive impairment is a well-documented concern among cancer survivors, yet the neural mechanisms underlying deficits in cognitive control remain poorly understood. This study examined group differences in brain activation during a flanker task using functional MRI (fMRI) between chemotherapy-exposed participants and healthy controls. MethodsParticipants (21 survivors (24.9 years old; 71.4 % female; 15 years from diagnosis) and 21 healthy controls (26.7 years old; 61.9 % female) completed a flanker task during fMRI, with congruent and incongruent conditions. Reaction time, accuracy, and Flanker scores were collected. Whole-brain group comparisons were performed for congruent, incongruent, and incongruent > congruent contrasts. Associations between the incongruent > congruent contrast and cognitive performance were examined. ResultsCompared to controls, the Chemo group had longer reaction times in both congruent and incongruent conditions (p < .001) and lower NIH Flanker scores (p = .01), with no differences in accuracy. They showed reduced activation in the bilateral inferior frontal gyri, supplementary motor area, and bilateral caudate, but greater activation in the right inferior temporal and cerebellar regions. The incongruent > congruent contrast correlated with increased activation in the orbitofrontal cortex, inferior temporal gyri, and fusiform gyrus with cognitive performance. ConclusionsChemotherapy-exposed participants showed cognitive control deficits and altered neural activation during a flanker task, indicating disrupted recruitment of frontoparietal and subcortical regions key for conflict processing. These findings improve understanding of neural causes of chemotherapy-related cognitive impairment and may help identify at-risk survivors and guide personalized rehabilitation.

neuroscience↗

bioRxiv2026

Multiple evidence supporting a novel species amid complex phylogenomic discordance: a case of Indian Ledebouria based on Angiosperms353 target capture sequencing

Ledebouria, a geophytic herb native genus to Africa and represented by a few species in the Arabian Peninsula, Madagascar, India and Sri Lanka. For a long time Indian species were named as L. revoluta until recent molecular work clarified African L. revoluta is distinct from Indian and Sri Lankan species. Hence the name L. hyacinthina was resurrected. However, there is no clear molecular or morphological clarification of the different morphotypes and karyotypes observed in various accessions from peninsular India. Since plastid DNA sequence markers failed to detect diversity, we used the high density, low copy number marker set, the Angiosperms353, for phylogenomic analysis of eight accessions and analysed with the same markers from the global dataset from published work. Our analysis shows L. hyderabadensis is a distinct species, whereas other widely distributed Indian accessions under the other name L. hyacinthina are young lineages representing incipient species. Our results indicate that Ledebouria has not diversified enough at the molecular sequence level for the marker set used. The same is also true of the chloroplast sequences.

evolutionary biology↗

bioRxiv2026

Dihydroartemisinin induces a two-step transcriptional response and stage-specific developmental shifts in malaria parasites, Plasmodium falciparum

The parasite Plasmodium falciparum causes malaria, the deadliest human parasitic disease, which remains fatal when not promptly treated. Evolving parasite resistance to frontline artemisinin-based therapies threatens vulnerable populations and decades of progress toward malaria elimination. Yet the mode of action of dihydroartemisinin (DHA), the active metabolite of these treatments, remains incompletely understood. Here we applied dose-response transcriptomics across the three intraerythrocytic stages - rings, trophozoites, and schizonts, revealing a two-tier transcriptional response to DHA, with low- and high-dose programs consistent with specific drug action and cytotoxic damage. The trophozoite stage mounts the strongest and most coordinated response, including a striking reversal of the developmental cascade in which protein synthesis machinery is broadly downregulated and a ring-like transcriptional profile is reactivated - reminiscent of drug-induced quiescence. Coordinated regulation of multiple protein complexes, most notably Kelch13 and its interacting partners (KIC), points to organized transcriptional control of the parasites drug response. This work provides a stage- and dose-resolved view of DHA action in P. falciparum and a template for future antimalarial mechanism-of-action studies.

Systems Biology↗

bioRxiv2026

Mycobacteriophage TM4 requires XylR for successful infection in Mycobacterium smegmatis mc2155

Mycobacteriophages are viruses that infect mycobacteria, including Mycobacterium tuberculosis, and have emerged as promising alternatives to antibiotics in the face of increasing antimicrobial resistance. However, evolution of phage-resistance remains a major challenge to the clinical implementation of phage therapy. We describe a TM4 phage resistant mutant in M. smegmatis harboring an in-frame deletion in the xylR, transcriptional regulator implicated in lipid metabolism, and cell envelope homeostasis. Using spontaneous mutagenesis, transcriptomics and biochemical approaches, we identify a previously uncharacterized resistance mechanism mediated by cell-envelope remodeling that impedes productive phage infection. The xylR mutation disrupted phage DNA injection through enhanced recruitment of lipooligosaccharides to the cell surface, without inhibiting phage adsorption, genome replication, and virion assembly. Remodeling of the cell envelope was further enhanced by the induction of lipooligosaccharide biosynthesis upon TM4 infection, however, the phenotype can be reverted through chemical treatment, restoring phage sensitivity. Our study expands the paradigm of innate mechanisms underlying broad-spectrum phage resistance in mycobacteria.

microbiology↗

bioRxiv2026

Rapid neural analysis of linguistic stress and meter in continuous speech

Continuous speech evolves around vowels, the centerpieces of individual syllables. Vowels vary in linguistic and acoustic salience: Linguistically, stressed syllables are more salient than unstressed syllables: Stress patterns convey critical lexico-semantic and prosodic information, and their regularity defines the speech meter. Acoustically, English vowel intensity cues lexical stress but also marks salient syllables irrespective of stress status. Recent evidence demonstrates rapid neural analysis of vowel intensity and identity during perception of continuous speech. Here, we probe how these processes integrate lexical stress and metrical regularity. We recorded EEG while participants (n=26) listened to childrens stories with either an irregular, speech-like meter, or a regular poetic meter. Stress and meter modulated cortical encoding of vowels throughout processing: Preparatory activity preceded vowel onsets in an irregular meter only, and early sensory responses were enhanced for unstressed vowels, suggesting additional resource allocation during processing of uncertain and less discriminable speech sounds. In contrast, later processing (300-500ms) was stronger for stressed syllables and in irregular meters, suggesting a combined effect of uncertainty and informational content. Finally, responses were stronger for small intensity rises within metrically predicted stressed vowels than in all other conditions. In the time-frequency domain, the spectral profile of neural phase-locking corresponded to spectral signatures of individual evoked responses, syllable and stress rates in the stimuli. Overall, our findings reveal rapid neural integration of stress and metrical expectations in neural processing of continuous speech. These dynamics may underlie the perceptual benefits of metrically regular speech, such as poetry and song lyrics.

neuroscience↗

bioRxiv2026

Integrative genomics of Plasmodium knowlesi reveals parasite-intrinsic regulators of severe human malaria

To dissect parasite determinants of clinical disease severity in Plasmodium knowlesi, we performed the first integrative genome-wide association (GWAS), transcriptomic, and expression quantitative trait locus (eQTL) analysis from clinical malaria isolates. We identify distinct parasite programs associated with WHO-defined severe disease, characterized by transcriptional activation of stress-response and host-interaction pathways. In contrast, invasion-linked programs were more strongly associated with parasite burden, while immune-evasion pathways showed overlapping but distinct associations with both burden and severity. GWAS and eQTL analyses revealed genetic regulation of transcriptional states, including immune-evasion variant antigen families (SICAvar and kir) and chromatin-associated regulators. Mature gametocyte transcripts were detectable across infections, including those with low parasitaemia, indicating that transmission-stage expression occurs independently of both clinical severity and parasite density. Together, these findings show that severe P. knowlesi malaria is associated with genetically regulated parasite transcriptional programs that are not fully explained by parasite burden.

genomics↗

bioRxiv2026

Determination of GLP-1 Secretion Potential of Dead and Live Akkermansia muciniphila Using Human L-cells

Background/ObjectivesGlucagon-Like Peptide-1 (GLP-1) is a key incretin hormone that regulates glucose homeostasis and energy metabolism. Impaired GLP-1 signaling contributes to the development of obesity, metabolic syndrome, and type 2 diabetes. Emerging evidence indicates that gut microbiota-derived components can influence GLP-1 secretion, highlighting the therapeutic potential of microbial modulators. Akkermansia muciniphila, a next-generation probiotic associated with improved metabolic health, remains underexplored for its capacity to stimulate GLP-1 release. This study aimed to investigate the GLP-1- stimulatory effects of live and pasteurized (dead) A. muciniphila strains in human enteroendocrine cells. MethodsHuman enteroendocrine L-cells (NCI-H716) were treated with varying doses of live and dead A. muciniphila from Vidya Herbss proprietary VHAKM strain and a commercially available marketed strain (dead form). Following incubation, GLP-1 levels were quantified from culture supernatants using enzyme-linked immunosorbent assay (ELISA). Comparative analyses assessed differences in GLP-1 secretion between strains and treatment forms. ResultsBoth live and pasteurized VHAKM strains significantly increased GLP-1 secretion compared to untreated controls. The live VHAKM strain exhibited higher GLP-1 stimulatory activity than its pasteurized counterpart and the marketed strain. The results suggest a strain-specific and viability-dependent modulation of GLP-1 secretion in human L-cells. ConclusionsThis study demonstrates that A. muciniphila VHAKM enhances GLP-1 secretion in a strain- and form-dependent manner, with live cells showing superior efficacy. These findings provide foundational insights for developing microbiome-targeted interventions to boost endogenous GLP-1 levels and improve metabolic health outcomes.

microbiology↗

bioRxiv2026

Multimodal antioxidant and anti-inflammatory activity of Rauwolfia serpentina root extracts in experimental models

BackgroundChronic inflammation and oxidative stress are central drivers of cardiovascular disease progression and remain incompletely addressed by existing pharmacological strategies. Traditional medicinal plants provide a valuable source of multi-target bioactive compounds that may modulate these interconnected pathways. Rauwolfia serpentina, a classical antihypertensive plant in Ayurveda, has been historically valued for cardiovascular indications. Yet, its antioxidant and anti-inflammatory actions beyond blood pressure regulation remain insufficiently characterised in immune-driven inflammatory models. MethodsRoot extracts of R. serpentina prepared using hot and cold ethanol and water were evaluated for antioxidant capacity using DPPH radical scavenging and phosphomolybdenum assays, along with phenolic, flavonoid, and terpenoid quantification. Protective effects against lipid peroxidation were assessed in rat liver and heart homogenates. Anti-inflammatory activity was examined in THP-1 human monocytic cells exposed to lipopolysaccharide (LPS), arachidonic acid (AA), and oxidative stress. Cytokine secretion and gene expression of TNF-, MCP-1, IL-6, and IL-8 were measured by ELISA and qRT-PCR. Intracellular reactive oxygen species and catalase activity were quantified to assess oxidative regulation. LC-MS-based metabolomic profiling was performed to characterise chemical diversity. The principal alkaloid, reserpine, was evaluated separately, and molecular docking was performed to examine its interaction with IKK. ResultsEthanolic extracts of R. serpentinas root, particularly the cold ethanolic fraction, showed superior antioxidant capacity, higher phenolic and flavonoid content, and potent inhibition of lipid peroxidation. These extracts markedly suppressed LPS-induced cytokine release and gene expression in THP-1 cells, with pronounced effects on MCP-1 and IL-6. Oxidative stress induced by arachidonic acid was attenuated through reduced intracellular ROS and preservation of catalase activity. Reserpine reproduced key features of the extract response, demonstrating strong suppression of IL-6 and MCP-1 at both transcriptional and secretory levels. Docking analysis indicated stable binding of reserpine within the IKK catalytic pocket, supporting a plausible mechanism for modulation of the NF-{kappa}B pathway. ConclusionR. serpentina root extracts exhibit coordinated antioxidant and anti-inflammatory activity in immune cell models relevant to cardiovascular inflammation. These effects are extraction-dependent and are partially mediated by reserpine through modulation of oxidative stress and inflammatory signalling pathways. The findings support the translational relevance of R. serpentina as a traditional medicine with mechanistic activity extending beyond antihypertensive action.

plant biology↗

bioRxiv2026

Integrative analysis of Myrcene's lipase inhibition and anti-inflammatory mechanisms in human monocytic cells

Myrcene (MCN), a monoterpene commonly present in essential oils of aromatic plants, was investigated for its dual role in modulating lipid metabolism and inflammation in human monocytic THP-1 cells. MCN was first evaluated for its ability to inhibit pancreatic lipase activity, followed by cytotoxicity screening to determine non-toxic working concentrations. Its anti-inflammatory effects were assessed by measuring TNF- gene expression and secretion in LPS-stimulated cells using qRT-PCR and ELISA, while NF-{kappa}B p65 nuclear translocation was examined through immunofluorescence. The influence of MCN on macrophage differentiation was further determined in PMA-treated THP-1 cells. MCN significantly reduced pancreatic lipase activity and suppressed inflammatory responses by downregulating TNF-, TLR2, and MIP-1, alongside preventing NF-{kappa}B p65 nuclear migration. Molecular docking supported these findings by confirming favorable interactions of MCN with the catalytic pocket of lipase and the nuclear localization region of NF-{kappa}B. Collectively, this study identifies MCN as a promising multitarget natural compound with potential therapeutic application in metabolic and inflammation-associated disorders. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=122 SRC="FIGDIR/small/699177v1_ufig1.gif" ALT="Figure 1"> View larger version (22K): org.highwire.dtl.DTLVardef@404f01org.highwire.dtl.DTLVardef@2e67aorg.highwire.dtl.DTLVardef@697050org.highwire.dtl.DTLVardef@4cb84d_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

bioRxiv2025

Enhancing the biocorrosion resistance and biocompatibility of Aluminium substrates using Graphene Oxide-PEDOT:PSS Hybrid Coating

Biofilm-associated infections on medical devices remain a major clinical challenge due to antimicrobial resistance, biofouling, and biocorrosion, compromising implant longevity and biocompatibility. Conventional biomedical devices utilizing stainless steel and titanium exhibit limited resistance to biofilm-prone physiological environments, necessitating development of next-generation implant materials. While alumina (Al2O3) is favored for its bio-inertness, it raises concerns like leaching and systemic toxicity. Aluminum alloy 1050 (AA1050) offers intrinsic corrosion resistance via a passive oxide layer under dry conditions but remains prone to microbiologically influenced corrosion (MIC) under humid conditions. In the recent years, graphene family of materials have emerged as promising surface coating for metals and alloys due to their strong barrier properties and antimicrobial efficacy. Most graphene derivatives like GO require relatively higher concentrations to achieve antimicrobial activity, however compromising biocompatibility, limiting in vivo human uses. This study addresses these caveats by exploring GO activity at lower concentrations (50-500 {micro}g/ml) on AA1050 to achieve a balance between antimicrobial efficiency and cytocompatibility. Additionally, poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS, 1 {micro}g/ml) was integrated with GO to form a hybrid coating on Al (Al_GO/P), to improve GO adhesion, and corrosion resistance. Biological evaluations against Escherichia coli (E. coli), Staphylococcus aureus (S. aureus), and Candida albicans (C. albicans) demonstrated superior antifouling and antimicrobial efficacy of Al_GO/P substrates compared to GO-coated Al (Al_GO) and bare Al surfaces. Corrosion rate, FESEM, ICP-MS, and cytotoxicity analyses further confirmed reduced biocorrosion, minimal ion leaching, along with enhanced biocompatibility of the hybrid coated surfaces. Al_GO/P containing GO at 100 and 250 {micro}g/ml concentration achieved the optimal balance between antimicrobial activity and biocompatibility and can be used as in vivo implant materials. Hence, this technology can be implemented towards surface modification of biomedical devices to mitigate periprosthetic infections as well as support ex vivo applications requiring durable antimicrobial performance.

microbiology↗

bioRxiv2025

Designing a robust whole-cell biosensor platform for detection of toxic metals using intein splicing inhibition of Mycobacterium tuberculosis SufB protein

Disruption of the natural geochemical cycle by human activities has led to bioaccumulation of metals, posing a global health threat. Hence, there is a pressing need for simple, sensitive, yet eco-friendly biosensor setups to monitor metal contamination in the environment. Existing biosensors are limited by poor efficiency, stability issues, and complex instrumentation requiring skilled operators. To address these caveats, current study explores how intein-mediated protein splicing, a spontaneous post-translational process, can be adapted for metal-biosensing by coupling metal-dependent splicing inhibition to viability loss of native microbial cells. Toxic metal ions like Cd2 and Hg2 attenuated the splicing activity of Mtb SufB precursor protein over a concentration range of 25 {micro}M to 2 mM, while Pb2 and Cr3 failed to do so. An innovative biosensor platform was designed for colorimetric detection of metal ions via simple Alamar Blue assay, where attenuated Mtb strain (H37Ra) served as the indicator cells. Metal-induced SufB splicing inhibition led to loss of viability of H37Ra cells, while addition of metal-specific chelators reversed the effect. Multiplexing ability was evaluated by including known splicing inhibitors like Cu2, Zn2, and Pt4 over various concentration range alongside Cd2 and Hg2. The simple 96-well plate format enables multiplexed qualitative metal detection, while colorimetric absorbance measurement ensures metal quantification. The designed biosensor offers low-cost, user-friendly, and sensitive assay for high-throughput metal detection, utilizing whole-cell native organisms carrying metal-sensing precursor protein. Thus, this approach can be implemented in standard biological laboratories for robust metal screening process in environmental and industrial effluents.

microbiology↗

bioRxiv2025

Enhanced Formulation of Precision Probiotics through Active Machine Learning

The human gut microbiome is crucial to health, with dysbiosis increasingly linked to disease. Precision probiotics offer a promising approach to restoring microbial balance, but ensuring probiotic viability through gastrointestinal transit remains a challenge. This study applies an advanced active machine learning (ML) approach to predict how excipients affect the growth of Lactobacillus plantarum, a commonly used probiotic. State-of-the-art experiments were carried out to complement the ML study. Starting with five known excipient- probiotic interactions, we apply active ML over three rounds to predict the effects of 116 excipients, iteratively refining model certainty and accuracy. Five ML models--Neural Networks, Gradient Boosting, Logistic Regression, Random Forest, and Support Vector Machines--were trained and evaluated, with the final model achieving certainty levels close to 90%. Unlike previous methods, which retrained new models per iteration, our approach continuously optimized a single model, enhancing prediction stability and reducing error. These results highlight the potential of active ML to support accurate excipient selection in probiotic formulations.

bioinformatics↗

bioRxiv2025

Robotic performance is comparable to human operators for cell therapy manufacturing tasks

Although numerous cell and gene therapies have received regulatory approval, their adoption has been hampered by high cost and challenges in scaling out manufacturing. Many autologous cell therapies are individually manufactured for each patient using traditional manual methods in high-cost environments. Therefore, robotics and automation offer a potential solution to meet the growing demand for such therapies. To ensure identical biological outcomes, automation must replicate validated manual workflows, a requirement that poses significant engineering challenges, especially for aseptic manipulation and compatibility with manual-centric instruments and consumables. Here we describe the design and performance of a modular robotic cluster consisting of specialized modules containing widely adopted equipment. The robotic arm uses custom end-effectors to handle standard consumables and instruments such as syringes, vials, bags, cell counters, bioreactors, incubators, and closed centrifuges. We compared the performance of skilled human operators against the robotic cluster across multiple tasks: transferring cells between sterile bags, cell counting, drawing volume from a vial to a syringe, and resuspension and sampling from both a bag and G-Rex 100M-CS bioreactor. The robotic system also executed high-complexity operations with industry-standard instruments: cell selection using a CytoSinct 1000 and wash/buffer exchange with a CTS Rotea Counterflow centrifugation system. Experimental results for each unit operation show that the robotic clusters performance is equivalent to manual operations on the selected key metrics. These data demonstrate that the robotic system can efficiently and robustly perform specific unit operations, which can be combined in any order for end-to-end cell therapy manufacturing processes. One Sentence summaryA modular robotic system can perform key unit operations in cell therapy manufacturing with accuracy comparable to human operators while ensuring throughput and flexibility.

bioengineering↗

bioRxiv2025

Polygenic Associations between Motor Behaviour, Neuromotor Traits, and Active Music Engagement in Four Cohorts

Phenotypic investigations have shown that actively engaging with music, i.e., playing a musical instrument or singing may be protective of motor decline in aging. For example, music training associated with enhanced sensorimotor skills accompanied by changes in brain structure and function. Although it is possible that the benefits of active music engagement "transfer" to benefits in the motor domain, it is also possible that the genetic architecture of motor behaviour and the motor system structure may influence active music engagement. This study investigated whether polygenic scores (PGS) for five behavioural motor traits, 12 neuromotor structural brain traits, and seven rates of change in brain structure traits trained from existing discovery genome-wide association studies (GWAS) predict active music engagement outcomes in four independent cohorts of unrelated individuals of European ancestry: the Canadian Longitudinal Study on Aging (CLSA; N=22,198), Wisconsin Longitudinal Study (WLS; N=4,605), Vanderbilts BioVU Repository (BioVU; N=6,150), and Vanderbilts Online Musicality study (OM; N=1,559). Results were meta-analyzed for each PGS main effect across outcomes and cohorts, revealing that PGS for a faster walking pace was associated with higher amounts of active music engagement. Within CLSA, a higher PGS for walking pace was associated with greater odds of engaging with music. Findings suggest a shared genetic architecture between motor function and active music engagement. Future intervention-based research should consider the genetic underpinnings of motor behavior when evaluating the effects of music engagement on motor function across the lifespan.

neuroscience↗