Biology subjects

Gupta, A.

Publications and source records attributed to Gupta, A..

At least 91 records · Page 5Linked to original sources

bioRxiv2025

A Case Study: Using Passive Acoustic Monitoring Devices In A Growing Urban Landscape To Monitor Avian Diversity

With the increase of urbanization around the world, key habitats such as grasslands and scrublands are disappearing, posing significant threats to species that rely on such habitats. Passive acoustic monitoring (PAM) has started to gain interest as a reliable tool for biodiversity monitoring. This study assesses whether PAM can be an effective way to monitor biodiversity with relatively low effort when compared to traditional survey methods. Using PAM, a mixed grassland and scrubland ecosystem was monitored for five months for avifaunal diversity. Data that was collected from dusk to dawn using audio recorders deployed on the study site were run through BirdNET analyzer under default detectors. Top detections for each species were compared with avian vocalization libraries manually. Out of 135 species detected, 76 were true positives, resulting in a species identification accuracy of 56.3%. Notably, among the species that were true detections, 21 species were found to have confidence scores larger than 0.99. In addition, 15 of the detected species were found to be migratory in this area, and three were found to be rare. This study demonstrates how PAM can be used to monitor biodiversity in a species-rich but understudied area such as Southern India, to identify both cryptic and nocturnal species that might be omitted from standard field surveys.

ecology↗

bioRxiv2025

Microbial Scl1 Activates TGFBR1 receptor kinase signalling to Drive Fibrosis-Inflammation Axis in Alcohol-Associated Liver Disease

Background and AimsAlcohol consumption alters gut microbiota, which can affect metabolism, immune regulation, and signalling pathways and lead to alcohol-associated liver disease (ALD). We investigated how alcohol-associated gut microbiota (AGMs) modulate liver kinome signalling to drive inflammation and fibrosis in ALD. MethodLiver kinome and metaproteome changes were studied in rats (n=6/group) colonized with stool of severe alcohol-related hepatitis (SAH) patients (SAH[->]healthy-rats) or healthy human donors (HD[->]ALD-rats). AGM-associated liver kinome changes were cross-correlated with bacterial genera. A bacterial protein; Streptococcal collagen-like protein 1 (Scl1) was identified with affinity for TGF{beta}R1. This was validated by molecular docking and immunoprecipitation-LCMS assay. Expression of Streptococcus pneumonia and pyogenes was done in stool of SAH patients (n=10). Also, Scl1 was quantified in patient stool (n=24) and liver tissue (n=19) samples. Validation was performed by assessing Scl1 level in plasma and Streptococcus level in stool samples before and after fecal microbiota transplantation (FMT) in SAH patients. ResultsStool metaproteomics showed significant increase in 10 bacterial genera (Streptococcus, Staphylococcus, and Clostridium) in SAH[->]Healthy-rats, mirroring changes seen in ALD-rats (FC>1.5, p<0.05). Clusters of Orthologous Groups analysis indicated increased post-translational modifications (PTMs) and decreased lipid metabolism in ALD-rats and SAH[->]Healthy-rats. Liver kinome profiling showed 85 upregulated kinases in SAH[->]Healthy-rats, with 34 overlapping with ALD-rats, associated with inflammation (Mapk14, Map3k10 and others), fibrosis (Tgfbr1, Igf1r, and others), lipid metabolism (Cdk14, Cdk18) and regeneration (Met, Bmpr1a and others). FMT from healthy human-donors to ALD-rats reversed the expression of Streptococcus (10-fold), Staphylococcus (3-fold), and Clostridium (5-fold), along with 18 kinases associated with inflammation (Btk, Camk4, Nuak1) and fibrosis (Tgfbr1, Col4a1, Fgfr2 and others). Strong association (r{superscript 2}>0.9, p<0.05) was seen between Streptococcus abundance and fibrosis and inflammation-related kinases. Level of Scl1 was significantly high in SAH and ALD-rat stool samples (FC>2, p<0.05). It showed strong affinity for TGF{beta}R1, as validated by molecular docking (>86%confidence) and immunoprecipitation assays (>100FC,p<0.05), indicating it as a potential ligand for TGF{beta}R1. Concordantly, expression of Scl1 was highest amongst all the known ligands for TGF{beta}R1 (p<0.05) suggesting Scl1 is a major contributor for TGF{beta}R1 activation and its downstream signalling in these patients. Following fecal microbiota transplantation, expression of Scl1 in plasma and Streptococcus levels in stool were significantly reduced by 2.1-folds and 1.9 folds respectively in SAH patients. Further, Scl1 levels SAH plasma is capable of predicting poor therapeutic response and 30-day mortality with high accuracy (AUC=0.92, cutoff >70 normalized abundance). ConclusionAlcohol induced gut dysbiosis alters the liver kinome, promoting inflammation, fibrosis, and lipid dysregulation. Streptococcal Scl1 is identified as a bacterial protein mimicking human collagen and capable of activating fibrotic signalling pathway through TGF{beta}R1in liver and is capable of predicting poor response in SAH. FMT from healthy donor restores microbial imbalance and harmful microbial-host interactions.

microbiology↗

bioRxiv2025

Representation Learning Methods for Single-Cell Microscopy are Confounded by Background Cells

Deep learning models are widely used to extract feature representations from microscopy images. While these models are used for single-cell analyses, such as studying single-cell heterogeneity, they typically operate on image crops centered on individual cells with background information present, such as other cells, and it remains unclear to what extent the conclusions of single-cell analyses may be altered by this. In this paper, we introduce a novel evaluation framework that directly tests the robustness of crop-based models to background information. We create synthetic single-cell crops where the center cells localization is fixed and the background is swapped--e.g., with backgrounds from other protein localizations. We measure how different backgrounds affect localization classification performance using model-extracted features. Applying this framework to three leading models for single-cell microscopy for analyzing yeast protein localization, we find that all lack robustness to background cells. Localization classification accuracy drops by up to 15.8% when background cells differ in localization from the center cell compared to when the localization is the same. We further show that this lack of robustness can affect downstream biological analyses, such as the task of estimating proportions of cells for proteins with single-cell heterogeneity in localization. Ultimately, our framework provides a concrete way to evaluate single-cell model robustness to background information and highlights the importance of learning background-invariant features for reliable single-cell analysis.1

bioinformatics↗

bioRxiv2025

IL-7 armed binary CAR T cell strategy to augment potency against solid tumors

Clinical studies of T cells engineered with chimeric antigen receptor (CAR) targeting CD19 in B-cell malignancies have demonstrated that relapse due to target antigen (CD19) loss or limited CAR T cell persistence is a common occurrence. The possibility of such events is greater in solid tumors, which typically display more heterogeneous antigen expression patterns and are known to directly suppress effector cell proliferation and persistence. T cell engineering strategies to overcome these barriers are being explored. However, strategies to simultaneously address both antigen heterogeneity and T cell longevity, while localizing anti-tumor effects at disease sites, remain limited. In this study we explore a dual antigen targeting strategy by directing independent CARs against the solid tumor targets PSCA and MUC1. To enhance functional persistence in a tumor-localized manner, we expressed the transgenic IL-7 cytokine and receptor (IL-7R) in respective CAR products. We now demonstrate the potency and durable antitumor effects of this binary strategy in a pancreatic tumor model.

immunology↗

bioRxiv2025

Phytofabrication of gold nanoparticles (AuNPs) via Wedelia chinensis Internodal extract: Characterization, Antioxidant, Antimicrobial, Hemolytic assay and Methylene Dye degradation properties

Wedelia chinensis is a medicinal herb of Asteraceae family. Preliminary phytochemical screening of internodal extract was done by using its aqueous, methanolic and ethanolic extracts. Preliminary phytochemical screening showed the presence of several pharmaceutically important compounds such as alkaloids, tannins, anthraquinons, saponins, flavonoids, terpenoids, phenols, etc. Aqueous internodal extract was used for the biosynthesis of gold nanoparticles. The characterization of gold nanoparticles were done by using a range of analytical techniques, such as energy-dispersive X-ray spectroscopy (EDS, EDX), X-ray diffraction (XRD), transmission electron microscopy (TEM), dynamic light scattering (DLS), Fourier transformed infrared spectroscopy (FTIR), scanning electron microscopy (SEM). The stability and other characteristics were ascertained using a UV-Vis spectrophotometer. The plasmon resonance occurred at the wavelength of 530 nm, thus showing the formation of gold nanoparticles. X-ray diffraction demonstrated the existence of Au-rich (fcc) phases in gold nanoparticles. FTIR analysis clearly indicated the participation of active constituents of internodal extract in the conversion of gold ions into AuNPs. DLS showed the size distribution (99.71 nm) of the suspended particles. There was variations in the sizes and shapes of the nanoparticles. The zeta potential of synthesized AuNPs was observed as -5.12 mV, thus showing the stability of the synthesized nanoparticles. In TEM study, uniform distribution of nanoparticles was seen with some agglomerates and average size of nanoparticles was observed in between 30-40 nm. The antioxidant potential of internodal extract was slightly higher than the synthesized gold nanoparticles. The green-synthesized AuNPs along with antibiotics demonstrated strong synergistic effect against several bacterial strains such as Escherichia coli and Bacillus subtilis. Gold nanoparticles showed good hemolytic activity against rat erythrocytes (90%). Gold nanoparticles also showed catalytic activity that reduces methylene blue at low concentration (1 mg). Highlights[tpltrtarr] Internodal extracts showed the presence of several active constituents in preliminary phytochemical screening. [tpltrtarr]Internodal extract was used for the synthesis of gold nanoparticles in one step process. [tpltrtarr]Synergistic action of AuNPs and antibiotics were reported against many pathogenic bacterial strains. [tpltrtarr]AuNPs showed its potential as antioxidant. [tpltrtarr]Hemolytic effect of nanoparticles was reported on rat blood sample. [tpltrtarr]Nanoparticles showed dye reducing activity thus enhancing its application in the purification of water bodies. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=159 SRC="FIGDIR/small/660090v1_ufig1.gif" ALT="Figure 1"> View larger version (38K): org.highwire.dtl.DTLVardef@12a27e3org.highwire.dtl.DTLVardef@a0d1b6org.highwire.dtl.DTLVardef@28178aorg.highwire.dtl.DTLVardef@216935_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFig.C_FLOATNO Graphical abstract of AuNPs C_FIG

plant biology↗

bioRxiv2025

Chenodeoxycholic Acid Modulation via Bacteroides intestinalis AM1 underscores a Novel Approach in Acute Liver Failure

BackgroundAcute liver failure (ALF) is associated with rapid and progressive hepatocellular injury, and severe metabolic-microbial derangements. We investigated early metabolic markers of non-survival, and a potential microbial intervention using Bacteroides intestinalis-AM1, to improve outcomes in ALF. MethodPlasma metabolomics and meta-proteomics were performed in 40 ALF patients and 5 healthy controls (training cohort). A non-survival marker panel was identified and validated in 270 ALF patients (test cohort) using high resolution mass spectrometry and machine learning. It was functionally validated in acetaminophen-induced ALF mouse model. B. intestinalis-AM1 was used to study alteration of gut bacteria and amelioration of liver injury. ResultsALF non-survivors showed a distinct metabolomic signature with elevated primary bile acids {chenodeoxycholic acid (CDCA), cholic acid (CA)}, tryptophan, tyrosine, and enrichment of pathways linked to inflammation, cell death, and stress response (p<0.01, FDR<0.01, FC>1.5). Non-survivors had higher alpha/beta diversity (p<0.05) with increase in Proteobacteria, Firmicutes, Actinobacteria (p<0.05); functionally associated with energy, amino acid and xenobiotic metabolism (p<0.05). A gut microbiota derangement in converting primary to secondary bile acids was evident as CDCA and cytotoxic metabolites (4-(2-Amino phenyl)-2,4-dioxobutanoate, L-Tyrosine) were higher. Elevated CDCA (logFC>10) levels correlated with mortality in ALF patients as well as in mouse model. In the later, administration of B. intestinalis-AM1 bacteria, (10^9) reduced CDCA and CA levels by enhancing FXR, FGF15, SLC10A1 gene expression, attenuating inflammation (IL-1beta, TLR4-signalling), necroptosis, and modulating glutathione(oxidative-repair), tryptophan(inflammation), and histidine (tissue repair) metabolism. ConclusionHigh levels of chenodeoxycholic acid (CDCA) represent a poor prognostic indicator in ALF patients. B. intestinalis-AM1, a primary-to-secondary bile acid converter, effectively reduce CDCA levels, activated FXR, reduced inflammation and protected hepatocytes, highlighting its therapeutic potential in ALF.

microbiology↗

bioRxiv2025

Stress-Induced Alteration of Small Extracellular Vesicles Drives Amyloid-Beta Sequestration and Exacerbates Alzheimer's Disease Pathogenesis

While small extracellular vesicles (sEVs) are implicated in amyloid-beta (A{beta}) trafficking, the mechanisms governing their interaction with A{beta} aggregates and plaque formation remain unresolved. Here, we report a paradigm-shifting discovery: sEVs undergo dynamic structural remodelling in response to stress, enabling selective binding to A{beta} aggregates-a phenomenon absent under normal physiological conditions. Using multimodal stressors, including mechanical (ultrasonication/agitation), physical (hyperthermia), and biological (oxidative damage), we demonstrate that stress-modified sEVs exhibit high-affinity binding to small A{beta} aggregates (SA) through scaffold reorganization, as validated by super-resolution microscopy and quantitative colocalization assays. Crucially, these remodelled sEVs act as potent carriers, enhancing SA internalization by neuronal cells in vitro. Strikingly, in post-mortem Alzheimers disease (AD) brains and APP-PS1 transgenic mice, sEVs were spatially enriched at amyloid plaque margins, suggesting a direct role in A{beta} sequestration and plaque expansion. Consistent with clinical relevance, sEVs isolated from AD patients exhibited an intrinsic SA-binding capacity, recapitulating stress-induced interactions observed experimentally. Our findings reveal that stress-primed sEVs function as pathological chaperones, binding to and internalizing A{beta} aggregates, thereby accelerating plaque nucleation and disease progression. This study provides the first evidence of stress-mediated sEV plasticity as a critical driver of A{beta} pathology, redefining therapeutic strategies targeting extracellular vesicle biology in neurodegenerative disorders. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=95 SRC="FIGDIR/small/655679v2_ufig1.gif" ALT="Figure 1"> View larger version (23K): org.highwire.dtl.DTLVardef@107c76borg.highwire.dtl.DTLVardef@1b56848org.highwire.dtl.DTLVardef@d18636org.highwire.dtl.DTLVardef@1c26db4_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2025

PURE: Policy-guided Unbiased REpresentations for structure-constrained molecular generation

Structure-constrained molecular generation (SCMG) generates novel molecules that are structurally similar to a given molecule and have optimized properties. Deep learning solutions for SCMG are limited in that they are pre-disposed towards existing knowledge, and they suffer from a natural impedance mismatch problem due to the discrete nature of molecules, while deep learning methods for SCMG often operate in continuous space. Moreover, many task-specific evaluation metrics used during training often bias the model towards a particular metric -"metric-leakage". To overcome these shortcomings, we propose Policy-guided Unbiased REpresentations (PURE) for SCMG that learn within a framework simulating molecular transformations for drug synthesis. PURE combines self-supervised learning with a policy-based reinforcement-learning (RL) framework, thereby avoiding the need for external molecular metrics while learning high-quality representations that incorporate an inherent notion of similarity specific to the given task. Along with a semi-supervised training design, PURE utilizes template-based molecular simulations to better explore and navigate the discrete molecular search space. Despite the lack of metric biases, PURE achieves competitive or superior performance than state-of-the-art methods on multiple benchmarks. Our study emphasizes the importance of reevaluating current approaches for SCMG and developing strategies that naturally align with the problem. Finally, we illustrate how our methodology can be applied to combat drug resistance, by identifying sorafenib-like compounds as a case study.

biochemistry↗

bioRxiv2025

Sustainable production of plastic-degrading enzymes in Chlamydomonas pacifica

The discovery of a new extremophile alga, Chlamydomonas pacifica, provides an opportunity to expand on heterologous protein expression beyond the traditional Chlamydomonas reinhardtii. C. pacifica is a unicellular extremophile capable of surviving at high pH, high temperatures, and high salinity. These various growth conditions allow C. pacifica to outcompete any invading contaminants in open-air environments. Developing this novel species as a platform for recombinant protein production could significantly advance commercial microalgal recombinant protein production. We have previously shown that C. reinhardtii can secrete a plastic-degrading enzyme: a PETase known as PHL7. This PETase is capable of cleaving ester bonds and has been used commercially for the degradation of PET plastics. However, the expression of such an enzyme has yet to be done in open raceway ponds and on a large scale. Here, we describe the culturing of PHL7 transgenic C. pacifica strain in three 80L raceway ponds and the measurements of recombinant enzymatic expression and activity found in the culture media. Our work provides proof of concept that this new organism can produce functional PHL7 enzymes in addition to producing the valuable components that inherently exist in the C. pacifica algae biomass. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=108 SRC="FIGDIR/small/654053v1_ufig1.gif" ALT="Figure 1"> View larger version (45K): org.highwire.dtl.DTLVardef@10065a3org.highwire.dtl.DTLVardef@110c456org.highwire.dtl.DTLVardef@1c9efc6org.highwire.dtl.DTLVardef@9ceea1_HPS_FORMAT_FIGEXP M_FIG C_FIG

synthetic biology↗

bioRxiv2025

Regulation of translational fidelity by repression of C/D box SNoRNPs during UPR

Endoplasmic reticulum (ER) is the major cellular compartment where the folding and maturation of secretory and membrane proteins take place. When protein folding demands exceed the protein handling capacity of ER, the unfolded protein response (UPR) pathway is activated. UPR reduces the client protein load in the ER by inhibiting protein translation and increases protein handling capacity by upregulating genes encoding ER-resident molecular chaperones. The main pathway for translational repression in response to ER stress has been the phosphorylation of eIF2 by PERK, which also suppresses rRNA synthesis. rRNA methylation and pseudouridylation can fine-tune protein synthesis. Small nucleolar ribonucleoproteins (SnoRNPs) are mainly separated into two subtypes: C/D box and H/ACA box. C/D box SNoRNPs guides rRNA 2-O-methylation, while H/ACA SNoRNPs catalyze the pseudouridylation modifications of rRNAs. We hypothesize that the UPR may regulate translational fidelity by regulating the expression of core proteins of C/D and H/ACA box SnoRNPs. In this study, we show that the expressions of NHP2L1, NOP56 and FBL were significantly downregulated by UPR. In addition, FBL knockdown reduced cell proliferation and colony formation. Furthermore, we show the effects of UPR and FBL knockdown on rRNA methylation and translation fidelity, including alterations in nonsense suppression, frameshifts, ribosome pausing and translation initiation by IRES. In conclusion, this study reveals the regulation of translational fidelity during UPR by change in rRNA methylation due to reduced function of C/D box SnoRNPs.

cell biology↗

bioRxiv2025

Low-Cost Screening of Algae for Extreme Tolerance to pH, Temperature, Salinity, and Light

Bioprospecting algae strains with tolerance to extreme conditions such as pH, temperature, salinity, and light is crucial for advancing biotechnology and environmental applications. However, traditional screening methods often involve significant costs and labor, restricting their accessibility and practical use. In this study, we developed and validated low-cost, high-throughput screening techniques, predominantly employing agar plates and liquid culture assays, to effectively differentiate tolerance levels among various algae strains. The methodologies were optimized using the model microalga Chlamydomonas reinhardtii and its closely related species Chlamydomonas incerta and the recently discovered extremophilic Chlamydomonas pacifica. We systematically evaluated the algae for tolerance to extremes by establishing precise gradients of pH (acidic to alkaline conditions), salinity (0 to 5 M NaCl), temperature (34-42{degrees}C), and light intensity (40 to 2977 E{middle dot}m-{superscript 2}{middle dot}s-{superscript 1}). Our results demonstrated that these cost-effective, agar plate-based methods effectively distinguished algae strains exhibiting superior tolerance to extreme environmental conditions. These screening techniques not only provided clear differentiation among the closely related strains but also delivered reproducible outcomes suitable for scaling up to larger bioprospecting efforts. Furthermore, the affordability and simplicity of these methods facilitate their implementation in resource-limited laboratories, thereby broadening participation in algae bioprospecting endeavors. This study highlights the potential of low-cost, accessible screening techniques to significantly enhance the discovery and characterization of algal strains with extreme traits. Ultimately, these methods support the development of robust algae-based resources, driving innovation in diverse industrial processes and environmental solutions. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=136 SRC="FIGDIR/small/653396v1_ufig1.gif" ALT="Figure 1"> View larger version (48K): org.highwire.dtl.DTLVardef@6b179borg.highwire.dtl.DTLVardef@dadbfforg.highwire.dtl.DTLVardef@a1750dorg.highwire.dtl.DTLVardef@baffc_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

bioRxiv2025

Control with Practical Guarantees of Stationary Variance in Stochastic Chemical Reaction Networks

Biomolecular integral feedback controllers offer precise regulation of molecular species copy numbers, making them valuable for synthetic biology applications. Antithetic integral feedback controllers, in particular, can be effective in low-copy-number regimes with stochastic dynamics. In this work, we introduce a modified variant of this controller, called the antithetic dual-rein integral feedback motif, and analyze its performance from a stochastic perspective in the presence of intrinsic dynamic randomness. We demonstrate that our controller enables first-moment control while maintaining a tractable steady-state variance bound under specific parametric regimes. Notably, this variance bound is tunable, as it depends solely on the controller parameters. We derive these results using stochastic model-order reduction and validate them through numerical simulations. Our findings provide new insights into achieving both precise regulation and noise suppression in stochastic genetic circuits.

synthetic biology↗

bioRxiv2025

Identification and Overexpression of Endogenous Transcription Factors to Enhance Lipid Accumulation in the Commercially Relevant Species Chlamydomonas pacifica

Sustainable low-carbon energy solutions are critical to mitigating global carbon emissions. Algae-based platforms offer potential by converting carbon dioxide into valuable products while aiding carbon sequestration. However, scaling algae cultivation faces challenges like contamination in outdoor systems. Previously, our lab evolved Chlamydomonas pacifica, an extremophile green alga, which tolerates high temperature, pH, salinity, and light, making it ideal for large-scale bioproduct production, including biodiesel. Here, we enhanced lipid accumulation in evolved C. pacifica by identifying and overexpressing key endogenous transcription factors through genome-wide in-silico analysis and in-vivo testing. These factors include Lipid Remodeling Regulator 1 (CpaLRL1), Nitrogen Response Regulator 1 (CpaNRR1), Compromised Hydrolysis of Triacylglycerols 7 (CpaCHT7), and Phosphorus Starvation Response 1 (CpaPSR1). Under nitrogen deprivation, CpaLRL1, CpaNRR1, and CpaCHT7 overexpression enhanced lipid accumulation compared to wildtype. However, CpaPSR1 increased lipid accumulation compared to wildtype in normal media despite causing no effect under nitrogen depravation, highlighting the difference in function based on media conditions. Notably, lipid analysis of CpaPSR1 under normal media conditions revealed a 2.4-fold increase in triglycerides (TAGs) compared to the wild type, highlighting its potential for biodiesel production. This approach provides a framework for transcription factor-focused metabolic engineering in algae, advancing bioenergy and biomaterial production. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=150 SRC="FIGDIR/small/651737v1_ufig1.gif" ALT="Figure 1"> View larger version (29K): org.highwire.dtl.DTLVardef@8ab995org.highwire.dtl.DTLVardef@19dff1forg.highwire.dtl.DTLVardef@1d865aborg.highwire.dtl.DTLVardef@1fafd12_HPS_FORMAT_FIGEXP M_FIG C_FIG Created with BioRender.com.

systems biology↗

bioRxiv2025

AntiCP3: Prediction of Anticancer Proteins Using Evolutionary Information from Protein Language Models

A number of computational methods have been developed in the past for predicting anticancer peptides, including AntiCP and AntiCP2 from our group. While these tools have been widely used by the scientific community, they are not suitable for predicting anticancer proteins. In this study, we present AntiCP3, the first dedicated method for the prediction of anticancer proteins. All models were trained using five-fold cross-validation and evaluated on an independent dataset not used during training. Our initial analysis revealed distinct compositional differences between anticancer peptides and proteins, justifying the need for a separate prediction framework. We first implemented similarity-based approaches, which yielded moderate performance. Subsequently, we developed machine learning and deep learning models using conventional protein features, achieving a maximum AUC of 0.72. The performance improved to an AUC of 0.79 with the incorporation of evolutionary information through PSSM profiles. Further enhancement was observed when embeddings from a fine-tuned protein language model ESM-t33 were used, leading to a best AUC of 0.90. Finally, a hybrid approach combining BLAST with our machine learning model achieved an AUC of 0.91. To facilitate the scientific community, we have implemented AntiCP3 as both a web server and standalone software for the prediction of anticancer proteins (https://webs.iiitd.edu.in/raghava/anticp3/). We have also deployed our model at hugging face https://huggingface.co/raghavagps-group/anticp3. Highlights Existing methods have been developed for predicting anticancer peptides. AntiCP3 is specifically optimised for predicting anticancer proteins. PSI-BLAST used to obtain evolutionary information in form of PSSM profile. Hybrid methods developed using alignment free and alignment based approach. A web server and standalone tool have been developed to assist the community.

bioinformatics↗

bioRxiv2025

Conserved inter-domain interactions drive trans-Golgi network localisation and trafficking of homologous copper-ATPases

Polytopic transmembrane Copper-ATPases are central regulators of the essential, redox-active micronutrient copper in all organisms. The vertebrate Cu-ATPase homologs ATP7A and ATP7B facilitate excess copper efflux, in addition to metalating cuproproteins. ATP7A and ATP7B exhibit copper-responsive basolateral and apical trafficking polarity respectively, in polarized epithelia. To elucidate the role of conserved functional domains in copper-responsive trafficking and copper transport, we substituted the copper-binding amino-terminal, Nucleotide-Binding (NBD) and C-terminal domain of ATP7B with that of ATP7A either singly or in combinations. The six chimeric Cu-ATPases generated, although functionally active, exhibited altered trafficking phenotypes. Notably, the N-terminal-substituted ATP7B exhibited constitutive trafficking to the basolateral membrane; however, the N-terminal and NBD double-substituted chimera gained steady-state TGN localization, indicating a putative interaction between the two domains critical for its TGN-localization. We analyzed orthologous Cu-ATPase domain sequences from diverse organisms and found that the N-terminal domain and NBD showed similar evolutionary relationships, unlike that of C-terminal domain, suggesting their co-evolution. This study for the first time correlates evolutionary stringency imparted onto Cu-ATPase domains with their significance in proper trafficking regulation.

cell biology↗

bioRxiv2025

Stretchable, hair-compatible, and long-term stable wearable EEG system

Electroencephalography (EEG) is a cornerstone in both neuroscience research and clinical diagnostics. However, conventional EEG monitoring faces hardware limitations, particularly its adaptability and stability. Headsets either require complicated wiring or do not have enough stretchability and wearability to comply with the diverse head anthropometry and hair conditions of the user population. Additionally, there is an inherent tradeoff between wet and dry electrodes in capturing high-fidelity signals from hair-covered scalp regions while ensuring continuous and long-term recording quality. Here, we present a Mesh-integrated, Stretchable, and Hair-compatible EEG system engineered to overcome these limitations. By incorporating a kirigami-inspired mesh design and stretchable eutectic Gallium-Indium interconnects, MindStretcH adapts to various head sizes and allows for easy wearing and removal. Moreover, its uniquely designed porous, conical, soft 3D-printed mold, embedded with hydrogel electrodes, effectively penetrates hair layers to deliver low impedance and sustained signal integrity with minimal discomfort. We validate MindStretcH through offline and online EEG-based brain-computer interface tasks over a month, demonstrating its exceptional stability in continuous monitoring and dynamic applications. These results mark a promising advance toward non-invasive neural interfaces in both clinical and everyday use.

bioengineering↗

bioRxiv2025

Pre-exposure to time-restricted feeding reduces tissue CD4+ T cells with limited effect on Mycobacterium tuberculosis clearance

Time-restricted feeding (TRF) in human and animal models positively impacts metabolic health by improving glucose homeostasis and reducing adiposity. However, limited studies have investigated the impact of TRF on the host immune response and upon bacterial infection. In this study, C57BL/6 mice (6-8 weeks old, male) were subjected to 8 hours of dark-phase TRF for 30 days, and aerosol infected with a low dose (100-400 colony-forming units) of Mycobacterium tuberculosis (Mtb) H37Rv. The body weight gain, multi-tissue metabolome, and proteome changes and distribution of immune cells in these study groups were monitored. In the first 15 days of TRF, mice showed better glucose tolerance with marginal weight loss. The serum and liver metabolome of TRF mice demonstrated perturbed fatty acid biosynthesis and degradation, steroid hormone biosynthesis pathways and tyrosine metabolism. Liver proteome data of TRF mice indicated an increased fatty acid oxidation which might affect the host immune cell frequency and functionality. The Mtb-infected TRF and control mice had similar tissue (lung, spleen and liver) bacterial burden at 21 days post-infection. The bone marrow of Mtb-infected TRF mice had significantly lower CD3+ T cells, and CD4+ T cells were low both in the bone marrow and lungs. This study reports that mice undergoing 8 hours of TRF had an improved metabolic phenotype, and discontinuing TRF limits its positive impact on handling Mtb infection at an early point.

immunology↗

bioRxiv2025

Evidence for balancing selection on loci associated with host use in the genome of a generalist plant parasite

Most research on host-parasite interactions has focused on tightly coevolved species pairs, yet many parasites are generalists that infect a wide range of host taxa. Generalist parasites are subject to highly variable selection pressures across different hosts and the footprints that this heterogeneous selection leaves in the genomes of generalists have been largely unexplored. To address this knowledge gap, we studied patterns of host-associated genetic diversity in the generalist plant parasite, the northern root knot nematode Meloidogyne hapla. By leveraging whole genome amplification, we generated whole genome libraries of individual root-knot nematodes collected from three different host plant species in a spatially replicated design. Despite finding no evidence of host-associated population structure, we did observe several hundred host-associated SNPs putatively under differential host selection. Genomic regions containing these host-associated SNPs were enriched for signals of balancing selection. Additionally, host-associated SNPs were enriched for functions involved in plant pathogenesis, specifically the modification of plant cell walls. Host-associated SNPs were also found in genes with known roles in dampening host plant immune responses to infection. Together, our results suggest a model of balancing selection in which heterogeneous selection by different host taxa maintains adaptive diversity at loci involved in pathogenesis.

evolutionary biology↗