Biology subjects

Das, B.

Publications and source records attributed to Das, B..

At least 19 recordsLinked to original sources

bioRxiv2026

Fitting and Selection of Within-Host Models for SARS-CoV-2 Infection

The main question in model selection for longitudinal RT-qPCR data is whether improvements in fit justify the additional parameters of more complex within-host models. We compared a target-cell-limited model (TIV), an eclipse-phase extension (TEIV), and a fractional-order TIV using infection waves reconstructed from SARS-CoV-2 cycle-threshold (Ct) measurements in a National Basketball Association cohort. Each trajectory was fitted on the Ct scale by maximizing a right-censored Gaussian likelihood using hybrid global-local optimization. Model selection was based primarily on the small-sample corrected Akaike information criterion (AICc), computed from the censored likelihood; while robustness to the choice of information criterion was assessed using the Akaike information criterion (AIC) and Bayesian information criterion (BIC). Among 868 evaluable trajectories, the unpenalized likelihood ranking identified TEIV as the clear best-fitting model in 34.0% of cases, fr-TIV in 30.2%, and TIV in 3.3%; the remaining 32.5% were effectively tied. After accounting for model complexity, AICc clearly favored TIV in 97.8% of trajectories and fr-TIV in 0.5%, while 1.7% were effectively tied; TEIV was not a clear winner in any of the trajectories. Thus, for these short, sparsely sampled Ct-only trajectories, TIV provided the best-supported parsimonious effective description. This does not imply that eclipse-phase or memory-like dynamics are biologically absent, but rather that the simpler TIV model is favoured by standard information criteria for the limited information contained in these data.

systems biology↗

bioRxiv2026

In vivo Quantitative Tomography of 225Ac Daughters in a Prostate Cancer Mouse Model with a Compton Camera

Targeted alpha therapy with 225Ac is a promising modality for cancer treatment, as shown in recent preclinical and clinical studies. Preclinical imaging of 225Ac is essential to fully understand the biokinetics of developmental 225Ac radiopharmaceuticals. Although single photon emission computed tomography (SPECT) is typically used to achieve this in vivo, conventional preclinical scanners struggle to provide high contrast and accurate quantification for 225Ac imaging due to the very low injected activities (below 1 kBq/g), the unfavorable gamma-ray branching ratios (<26%), and its complex decay chain with several gamma-ray emissions. In this work, we employ a compact CZT-based Compton camera to achieve quantitative tomography of 225Ac daughters in live mice at 18.5 kBq (0.5 Ci) injected activities. Three mice bearing 22Rv1 prostate cancer subcutaneous xenografts were scanned in a single bed position for 30 minutes following intravenous administration of 18.5 kBq of the Anti-CD46 225Ac-Macropa-PEG4-YS5 conjugate. We successfully visualized the in vivo biodistributions of the 225Ac daughters 221Fr and 213Bi, distinguishing between the tumor xenograft and the central organs. Quantification of the tumor uptake from the images revealed an activity as low as 1.1 kBq. In vivo activity quantification computed from the images was compared to ex vivo biodistribution measurements using a gamma counter after harvesting the tissue, showing strong agreement.

bioengineering↗

bioRxiv2026

Orthoflaviviruses use diverse binding modes to engage LDLR family receptors

Orthoflaviviruses are major human pathogens that cause substantial morbidity and mortality worldwide. The viral envelope (E) mediates entry of orthoflaviviruses into host cells by interacting with cellular receptors, including members of the low-density lipoprotein receptor (LDLR) family. Here, we determined cryo-electron microscopy (cryo-EM) structures of yellow fever virus (YFV) E bound to low-density lipoprotein receptor-related protein 4 (LRP4) and LRP8, and of tick-borne encephalitis virus (TBEV) E bound to LRP8. Structural and functional studies reveal that YFV engages two low-density lipoprotein receptor class A (LA) repeats of LRP4 and LRP8 primarily through domain III (DIII) and the DI-DIII linker of its E protein, with each LA repeat making distinct contacts. In contrast, TBEV relies on a distinct surface on domain II (DII) of its E protein to interact with LRP8. Despite these differences, both viruses require engagement of two sequential receptor LA repeats for binding. Our findings identify key determinants of receptor specificity for these two orthoflaviviruses, with implications for vaccine development and therapeutic antibody targeting.

microbiology↗

bioRxiv2026

Loss of PTPRB function remodels VEGFR1 activation in tumors overexpressing the receptor tyrosine kinase

The VEGF Receptor-1 (VEGFR1) is a deceptive receptor tyrosine kinase (RTK). In early embryonic development, VEGFR1 negatively regulates angiogenesis by acting like a decoy receptor. Ligand binding transiently phosphorylates the receptor and induces a weak activation, even at high receptor density. Yet, in multiple cancers, overexpression of VEGFR1 plays a central role in tumor vascularization and growth. Unlike many pro-oncogenic RTKs, extensive patient data analysis revealed no somatic mutation in VEGFR1 that may spontaneously activate the tyrosine kinase. The mechanism by which VEGFR1 is activated in cancers has remained an open question for more than two decades. Here, we evaluated the multi-omics profiles of VEGFR1 and its regulators in a pan-cancer database. We observed an inverse correlation between VEGFR1 and PTPRB phosphatase expression in KIRC patients and disease outcome. We observed that patients overexpressing VEGFR1 and deficient in PTPRB expression have a lower likelihood of survival. Using super-resolution single-cell imaging, we discovered that inhibiting PTPRB spontaneously activates VEGFR1 by inducing ligand-independent dimerization, possibly by shifting the equilibrium toward the active state. PTPRB inhibition induces sustained, ligand-dependent phosphorylation of VEGFR1, which may promote tumor vascularization. We conclude that a subtle phosphatase imbalance is fundamental in determining VEGFR1s role in pathological angiogenesis in tumors.

biochemistry↗

bioRxiv2026

Genetic Diversity and Population Structure of Maize Doubled Haploid Lines from Drought and Low Nitrogen Tolerant Populations

Understanding the genetic diversity and population structure of breeding materials is essential for developing stress-resilient cultivars. In tropical maize, where drought and low soil nitrogen (low N) severely limit productivity, continuous development of tolerant varieties remains a priority. This study assessed the genetic diversity and population structure of 250 doubled haploid lines (DHLs) derived from five drought- and low N-tolerant tropical populations. Genotyping was performed using mid-density DArTseq markers, yielding 3,305 high-quality SNPs for analysis. Results revealed a moderate level of diversity among the DHLs, with an average genetic distance of 0.39, a polymorphism information content (PIC) of 0.33, and a minor allele frequency (MAF) of 0.29. These values reflect substantial allelic variation, important for identifying complementary parental combinations in hybrid development. Discriminant analysis of principal components (DAPC) grouped the DHLs into five distinct clusters, largely corresponding to their source populations, although some admixture was observed. This indicates that while the genetic backgrounds of the source populations were mostly retained, recombination introduced useful variation. Overall, the clear population structure and high diversity observed among these DHLs provide a strong genetic foundation for future maize improvement. These lines represent valuable resources for heterotic group formation, hybrid development, and recurrent selection schemes aimed at enhancing drought and low nitrogen tolerance in tropical maize.

genetics↗

bioRxiv2026

Lachesin is a mosquito receptor for multiple arthritogenic alphaviruses

Arthritogenic alphaviruses cause acute febrile illnesses associated with rash and arthritis when they are transmitted to humans through the bite of infected mosquitoes. Among these, chikungunya virus (CHIKV), transmitted primarily through the bite of infected Aedes aegypti and Aedes albopictus mosquitoes, causes explosive outbreaks involving hundreds of thousands to millions of cases, with recent re-emergence in several global regions. While several cellular receptors that mediate alphavirus entry into mammalian cells have been identified, their mosquito counterparts remained unknown, largely due to a lack of functional genomics tools for these invertebrate species. Here, we established a CRISPR-based genetic screening platform in Aedes albopictus cells and used it to identify Lachesin, a conserved invertebrate cell adhesion molecule, as a receptor for CHIKV and multiple related alphaviruses including Semliki Forest virus (SFV), onyong-nyong virus (ONNV), Mayaro virus (MAYV), and Ross River virus (RRV). Lachesin depletion using RNA interference, anti-Lachesin antibody treatment, and soluble forms of Lachesin blocked CHIKV and SFV E2-E1 glycoprotein-mediated infection of mosquito cells. We show that alphavirus E2-E1 glycoproteins bind the first immunoglobulin domain of Lachesin, facilitating attachment and internalization of virus-like particles. Orthologs from divergent mosquito genera, but not from arachnids or other arthropods, also serve as alphavirus receptors, suggesting that cellular receptor binding is not the main obstacle to arthritogenic alphavirus vector host expansion. Our findings enhance understanding of the mechanisms of alphavirus emergence and vector competence and could aid in the development of broadly active, entry-targeted therapeutics against multiple alphaviruses that threaten public health.

microbiology↗

bioRxiv2026

Target-Specific Discovery of BMM_1567 Restores Aminoglycoside Activity Against Multidrug-Resistant Gram-Negative ESKAPE Pathogens

The global emergence of multidrug-resistant (MDR) ESKAPE pathogens has significantly reduced the effectiveness of existing antibiotics, highlighting the urgent need for new strategies to restore antimicrobial susceptibility. Here, we report the discovery and mechanism of BMM_1567, a peptide potentiator that enhances aminoglycoside efficacy against MDR pathogens. A genetically defined reporter-based screen identified BMM_1567 as a potent inhibitor of aminoglycoside resistance, potentiating spectinomycin activity against MDR Gram-negative ESKAPE isolates at low micromolar concentrations. Structural modeling and molecular dynamics simulations indicated that BMM_1567 interacts with residues lining the antibiotic-binding groove of aminoglycoside-modifying enzymes (ANT, APH, AAC), with highest affinity for ANT ({Delta}G_bind = -62.25 kcal/mol), suggesting competitive inhibition of substrate binding. Site-directed mutagenesis of key ANT residues identified critical amino acids involved in BMM_1567 binding, confirming their role in mediating spectinomycin potentiation. In murine abscess model using XDR E. coli, BMM_1567 in combination with spectinomycin significantly reduced bacterial burden and pro-inflammatory cytokine levels, comparable to colistin. Collectively, these findings establish BMM_1567 as a promising aminoglycoside potentiator that restores antibiotic activity against MDR pathogens through direct inhibition of resistance enzymes, while exhibiting in vivo efficacy and a remarkably low propensity for resistance development.

microbiology↗

bioRxiv2026

Integrated transcriptomic and proteomic analyses identify novel biomarkers of bladder outlet obstruction

Bladder outlet obstruction leads to pathological remodeling and emergence of lower urinary tract symptoms. Although relief of obstruction is associated with symptomatic improvement, it is not universally successful, reflecting persistent alterations in the bladder. Reliable surrogate biomarkers of obstruction are lacking, particularly early in the disease course before irreversible damage to the bladder may have occurred. In this study, re-analysis of publicly available transcriptomic datasets from diverse rodent models of obstruction identified tissue transcripts including Cthrc1, Grem1, Ltbp2 and Msn that were induced in response to injury. Candidate markers were validated experimentally in an independent model of neurogenic obstruction demonstrating time-dependent changes. Candidate markers were also attenuated with either surgical removal of obstruction or treatment with anticholinergic medication or inosine. Integrated analysis of tissue transcriptomics data and tissue and urine proteomics data from a model of neurogenic obstruction revealed significant concordance between markers observed in tissue and urine. Urinary proteomics analysis identified a statistically significant increase in MSN in patients with neurogenic bladder compared to unaffected controls. These findings identify tissue and urine biomarkers of both non-neurogenic and neurogenic obstruction that may reflect early changes in obstructive uropathy that could be monitored in a non-invasive manner.

bioinformatics↗

bioRxiv2026

Rhythmic gene expression and behavioral plasticity in harvester and carpenter ants

We examined the overlap in the genes associated with daily rhythms and with behavioral plasticity in ants. We first investigated the daily rhythms of gene expression in the harvester ant, Pogonomyrmex barbatus, and how the rhythmic genes overlap with others previously shown to be associated with plasticity of foraging behavior. Then, to consider whether the overlap is conserved across ant species, we compared rhythms of gene expression in the diurnal, desert harvester ants with those previously reported for a distantly related nocturnal, subtropical carpenter ant, Camponotus floridanus. First, daily transcriptomes in P. barbatus showed that most genes were expressed in light-dark (LD) and constantly dark (DD) conditions at about the same levels; only 11 genes showed at least a two-fold change in expression. Network analysis identified eleven modules of P. barbatus genes under LD conditions. Of these 11 clusters, modules C1 and C2 seem to be central nodes of the gene expression network, because they are the most highly connected in LD, and show the strongest preservation in DD vs. LD, and contain core clock gene Period. Only one module, C2, showed significant overlap with P. barbatus genes that have 24h-rhythmic expression in both LD and DD. There was significant overlap between modules C1, C2, C10, C11, and P. barbatus genes found previously to be associated with plasticity in the regulation of foraging activity to manage water loss. A comparison of the daily transcriptome of P. barbatus with that of C. floridanus showed significant overlap of 24h-rhythmic genes in LD. Modules C1 and C2 of P. barbatus also overlap with C. floridanus genes previously shown to differ in expression rhythms in nurses and foragers. In combination, these results indicate that genes linking plasticity of the circadian clock and of behavior may be broadly conserved in ants.

systems biology↗

bioRxiv2026

Biodiversity Dimensions in Mangroves: Uncovering Interactions and Spatial Drivers in the Sundarbans

Mangroves play a crucial role in supporting global biodiversity and ecosystem functioning, yet how their multidimensional diversity interact and respond under diverse stress conditions remains underexplored. To address this gap, using species, environmental, functional trait and forest structural data collected from the permanent sample plot (PSP) network (110 PSPs) of the worlds largest mangrove ecosystem, the Sundarbans, we answer three key questions: (Q1) How are structural, functional, taxonomic, and phylogenetic diversities interconnected? We hypothesized that these diversity components are positively correlated (H1). (Q2) What are the key environmental stressors and how the diversity components are influenced by multiple stressors? We hypothesized that these stressors negatively affect all diversity components (H2). (Q3) What spatial patterns emerge in the distributions of these diversity components? Here we hypothesized that these diversity components vary across space under changing environmental conditions (H3). Our results show that taxonomic, functional, structural, and phylogenetic diversity have varying degrees of interconnection. While taxonomic and structural diversity are strongly correlated, functional and phylogenetic diversity exhibit more independent patterns, suggesting distinct ecological processes shape each dimension. Salinity, elevation, silt, community structure and downstream-upstream gradient (i.e., upriver position) have strong influences on all the diversity components although the magnitude of the influence varies. GAM results reveal that salinity and siltation act as the primary negative drivers for most dimensions; however, functional richness and divergence show a unique positive response to salinity. Furthermore, we found that community structure and upriver position significantly influence diversity patterns, often in a non-linear fashion. Though taxonomic, structural, and phylogenetic diversity show higher values mainly in the moderate and low saline areas, functional richness shows higher values in high saline areas. Overall, our results provide strong support for all the hypotheses. Our findings highlight the importance of holistic approach integrating taxonomic, structural, functional, and phylogenetic dimensions for maintaining biodiversity and ecosystem functions in dynamic mangrove ecosystems and emphasize the need for conservation efforts that target moderate-stress zones to preserve both ecological and evolutionary diversity. HighlightsO_LIExplored the interconnection between four dimensions of biodiversity (taxonomic, structural, functional, and phylogenetic) and how they respond to multiple stressors in the worlds largest mangrove forest. C_LIO_LIHigh salinity and siltation act as the primary environmental stressors that negatively affect overall biodiversity. C_LIO_LIStructural diversity is strongly related to species richness, serving as a key indicator of ecosystem health. C_LIO_LIFunctional and phylogenetic diversity follow independent spatial patterns, promoting the need for multi-dimensional monitoring. C_LI

ecology↗

bioRxiv2025

BLMPred: predicting linear B-cell epitopes using pre-trained protein language models and machine learning

B-cells get activated through interaction with B-cell epitopes, a specific portion of the antigen. Identification of B-cell epitopes is crucial for a wide range of clinical applications, including disease diagnostics, vaccine and antibody development, and immunotherapy. While experimental B-cell epitope identification is expensive and time-consuming, computational tools are starting to emerge that can generate lists of high-confidence epitopes for experimental trials. In this paper, we present BLMPred, a sequence-based linear B-cell epitope prediction tool, which exploits pretrained protein Language Model embeddings for deriving local and global protein structural features from the protein primary structure. BLMPred is a binary classifier which can predict whether an input peptide sequence is an antibody epitope or not without relying on 3D protein structures. BLMPred has been shown to outperform other comparable tools when tested on multiple independent datasets. It is freely available at https://github.com/bdbarnalidas/BLMPred.git.

bioinformatics↗

bioRxiv2025

ABCDscores: An R package for computing summary scores in the ABCD Study(R)

The ABCD Study(R) is the largest longitudinal research study of brain development and child health across the United States. The study generates a rich multimodal dataset, including file-based raw and derivative data and a curated tabulated dataset comprising data from a broad spectrum of research domains. Historically, summary scores in the tabulated dataset were computed using the electronic data capture system REDCap or external scripting solutions. However, this approach was rigid, unreliable, and lacked transparency around how scores were computed. Here, we introduce ABCDscores, an R software package that is used by the study to compute most non-proprietary summary scores included in the tabulated ABCD data resource and allows for customization to meet specific research needs. ABCDscores provides a flexible, open-source solution that uses R for transparent and reproducible scoring. The package is built to apply standard scoring methods across different types of assessments, ensuring consistent and accurate results even with large datasets. By simplifying complex scoring procedures into a user-friendly process, ABCDscores streamlines research workflows, reduces errors, and saves researchers valuable time. The package aims to improve analyses of data from the ABCD Study(R) and can serve as a model for the development of similar tools and a standardized framework for other research studies, fostering new discoveries and innovation in the field.

bioinformatics↗

bioRxiv2025

Capturing the Mutational Dynamics of SARS-CoV-2 with Graphs

The rapid evolution of SARS-CoV-2 presents significant challenges for modeling viral dynamics, driven by lineage diversification and region-specific mutation patterns. While phylogenetic trees are traditionally used for evolutionary inference, the massive volume of SARS-CoV-2 genomic data, with many similar sequences and few distinguishing mutations, poses computational and methodological limitations. The quasispecies theory instead models viral evolution as a cloud of mutants, motivating a graph-based representation that better captures the complexity of mutational events. Geographic variation adds another critical layer to this complexity. Mutation trends often differ across regions due to local transmission dynamics, host population structures, and selective pressures. In this study, we present the Mutation Learning Graph (MLG), a directed graph framework that organizes SARS-CoV-2 variants based on their cumulative mutation profiles relative to the reference genome (NC_045512.2), thereby capturing the dynamics of mutation propagation. This structure captures fine-grained mutational transitions and encodes plausible evolutionary relationships among variants. To construct these graphs, we introduce an alignment-aware mutation profiling method and a novel AO_SCPLOWNCESTORC_SCPLOW-JO_SCPLOWOININGC_SCPLOW algorithm, which incorporates ancestral variants as inferred intermediate nodes to connect observed genomes through biologically coherent mutational paths. We generate MLG datasets for ten geographically and epidemiologically diverse regions and benchmark them on two graph-based tasks: node-level lineage classification and edge-level mutational transition prediction. Using baseline graph neural network architectures (GCN, GraphSAGE, GAT, GGNN, VGAE), we demonstrate how mutation-centric graph structures expose key biological challenges, such as lineage imbalance and location-specific mutation spectra. For node classification, GraphSAGE and GGNN consistently achieved high accuracy (up to 0.96) and AUROC (up to 0.98). In contrast, VGAE and GraphSAGE led the way in link prediction, with AUPRCs of up to 0.96. These results highlight the effectiveness of MLG for capturing biologically meaningful mutation patterns and underscore the importance of localized, mutation-aware modeling for predicting viral mutations and future variant emergence.

bioinformatics↗

bioRxiv2025

Fano factor as a key measure of sensitivity in biological networks

Sensitivity of a biological process is vital for its proper function and regulation. Biological networks in equilibrium display such sensitivity mainly through cooperative binding of ligands to network elements comprised of multiple sites of an oligomeric protein. The classical measure of binding cooperativity is the Hill slope obtained empirically from binding isotherm data, known as the Hill plot. Hill slope value greater (less) than unity indicates positive (negative) cooperativity. In this study, we have shown that the Hill slope is actually a combination of two Fano factors associated with the number of bound and empty sites of the network, respectively. Taking a ladder network capable of showing positive cooperativity only, we have analytically proved that if the variation of Fano factors with fractional saturation of the network is non-linear, the binding is cooperative and if the variation is linear, the binding is non-cooperative with Hill slope equal to unity. Further, through numerical analyses of a linear network that can exhibit both positive and negative cooperativity, it is established that the curves of Fano factor for the positive (negative) cooperative cases reside above (below) the line representing the non-cooperative case. Our results, thus, confirm the role of Fano factor as the crucial measure of sensitivity in biological networks.

biophysics↗

bioRxiv2024

Shroom3-Rock interaction and profibrotic function: Resolving mechanism of an intronic CKD risk allele.

Common intronic enhancer SNPs in Shroom3 associate with CKD in GWAS, although there is paucity of detailed mechanism. Previously, we reported a role for Shroom3 in mediating crosstalk between TGF{beta}1- & Wnt/Ctnnb1 pathways promoting renal fibrosis (TIF). However, beneficial roles for Shroom3 in proteinuria have also been reported suggesting pleiotropic effects. Here we focused on identifying the specific profibrotic Shroom3 motif. Given known therapeutic roles for Rho-kinase inhibitors in experimental CKD, and the established interaction between Shroom3 and Rock via its ASD2 domain, we hypothesized that Shroom3-mediated ROCK activation played a crucial role in its profibrotic function in high expressors. To test this hypothesis, we developed transgenic mice and cell lines that inducibly overexpressed wild-type- (WT-Sh3) or ASD2-domain deletion- Shroom3 (ASD2{Delta}-Sh3). Prior scRNAseq data showed that during TIF, Shroom3 and Rock co-expression occurred in injured tubular cells and fibroblasts, highlighting cell-types where this mechanism could be involved. Using HEK293T cells, we first confirmed absent ROCK binding and inhibited TGF{beta}1-signaling with ASD2{Delta}-Sh3-overexpression vs WT-Sh3. In mIMCD cells, ASD2{Delta}-Sh3 overexpression, reduced Rock activation (phospho-MYPT1), pro-fibrotic and pro-inflammatory transcripts vs WT-Sh3. Fibroblast proliferation (3T3) was also reduced with ASD2{Delta}-Sh3. In vivo, we studied ureteric obstruction (UUO) and Aristolochic nephropathy (AAN) as TIF models. In AAN, inducible global-, or Pan-tubular specific-, WTSh3-overexpression showed increased azotemia, and TIF vs ASD2{Delta}-Sh3 mice. WT-Sh3 mice consistently showed significant enrichment of Rho-GTPase, TGF{beta}1- and Wnt/CtnnB1- signaling in kidney transcriptome, paralleling Shroom3-coexpressed genes in tubulo-interstitial transcriptomes from human CKD. In UUO, again WT-Sh3 mice recapitulated increased fibrosis vs ASD2{Delta}-Sh3. Importantly, ASD2{Delta}-Sh3 did not develop albuminuria vs WT-Sh3, while mutating a disparate Fyn-binding Shroom3 motif induced albuminuria in mice, suggesting motif-specific roles for Shroom3 in the kidney. Hence, our data show a critical role for the Rock-binding, ASD2-domain in mediating TIF in milieu of Shroom3 excess, with relevance to human CKD.

systems biology↗

bioRxiv2024

Variant Evolution Graph: Can We Infer How SARS-CoV-2 Variants are Evolving?

The SARS-CoV-2 virus has undergone mutations over time, leading to genetic diversity among circulating viral strains. This genetic diversity can affect the characteristics of the virus, including its transmissibility and the severity of symptoms in infected individuals. During the pandemic, this frequent mutation creates an enormous cloud of variants known as viral quasispecies. Most variation is lost due to the tight bottlenecks imposed by transmission and survival. Advancements in next-generation sequencing have facilitated the rapid and cost-effective production of complete viral genomes, enabling the ongoing monitoring of the evolution of the SARS-CoV-2 genome. However, inferring a reliable phylogeny from GISAID (the Global Initiative on Sharing All Influenza Data) is daunting due to the vast number of sequences. In the face of this complexity, this research proposes a new method of representing the evolutionary and epidemiological relationships among the SARS-CoV-2 variants inspired by quasispecies theory. We aim to build a Variant Evolution Graph (VEG), a novel way to model viral evolution in a local pandemic region based on the mutational distance of the genotypes of the variants. VEG is a directed acyclic graph and not necessarily a tree because a variant can evolve from more than one variant; here, the vertices represent the genotypes of the variants associated with their human hosts, and the edges represent the evolutionary relationships among these variants. A disease transmission network, DTN, which represents the transmission relationships among the hosts, is also proposed and derived from the VEG. We downloaded the genotypes of the variants recorded in GISAID, which are complete, have high coverage, and have a complete collection date from five countries: Somalia (22), Bhutan (102), Hungary (581), Iran (1334), and Nepal (1719). We ran our algorithm on these datasets to get the evolution history of the variants, build the variant evolution graph represented by the adjacency matrix, and infer the disease transmission network. Our research represents a novel and unprecedented contribution to the field of viral evolution, offering new insights and approaches not explored in prior studies.

bioinformatics↗

bioRxiv2024

Distance between miRNA responsive elements selectively enhances target specificity with reduced cellular toxicity by miRNA-mediated synergism

Despite the emergence of miRNAs as promising therapeutic tools in cancer management, most clinical trials have not been successful due to their cytotoxic effects. Here, we have investigated the factors regulating the effect of miRNA-mimic pairs in enhancing target gene specificity while reducing cellular toxicity. Synergistic reductions by the miRNA-mimic pairs were observed for the 3-UTRs of common target genes with miRNA-responsive elements (MREs) preferentially located at a distance of 200-800bp. Deletion of either of the miRNA seed sequences resulted in a loss of synergism. Furthermore, we performed small RNA-sequencing to identify significantly downregulated miRNAs in Oral cancer. Consequently, we transfected let-7c-5p and miR-125b-5p miRNA mimics either alone or in combination at half-dose concentrations and determined the expression levels of their common and unique target genes in oral cancer cells. Significant reductions in target gene expression were observed for genes containing MREs for both miRNA mimics within the preferential distance. Proteomic data revealed that the let-7c-5p and miR-125b-5p miRNA-mimic pairs synergistically reduced the expression of their common target genes, hexokinase 2 (HK2) and branched-chain amino acid transaminase 1 (BCAT1), in cancer cells. However, unique target genes did not exhibit any significant alterations in their protein levels. The effect of HK2 and BCAT1 downregulation was also reflected in the metabolomic profiling of cancer cells, specifically affecting glycolysis and the BCAA degradation pathways. As a result of the metabolic impairment caused by the synergistic effect of miRNA mimic pairs, oral cancer cells showed a significant reduction in proliferation, migration, and spheroid formation compared to cells treated with either single miRNA. The synergistic effect of these miRNA mimics was lost in normal keratinocytes, possibly due to low expression levels of the target oncogenes, suggesting a cancer cell-specific effect of this mechanism.

cancer biology↗

bioRxiv2024

Comparative Analysis of Antioxidant Activity, ROS, and Relative Water Content Between Red and Green Cabbage

Cabbage, the second largest leafy vegetable, is highly valued for its nutritional richness and versatility. As health consciousness increases, the worldwide demand for cabbage continues to grow steadily. Cabbages come in various forms, varying in size, color, texture, and nutritional properties. An experiment was conducted to distinguish significant differences in relative water content (RWC of leaf and RWC of head), relative oxygen species (MDA and H2O2), and antioxidant properties (POD, APX, and CAT) between red and green cabbage varieties. Cabbage samples were grown under fertilizer and control conditions to observe the impact of fertilizers on the acquisition of these properties. The results indicated that fertilizer application positively influenced the acquisition of relative water content, relative oxygen species, and antioxidant properties in both cabbage varieties. The results emphasized that red cabbage excelled in antioxidants and ROS levels, containing higher amounts compared to green cabbage. Conversely, green cabbage showed greater relative water content in both cultivation conditions. These findings suggest that consumers seeking higher antioxidant and ROS levels in their diet may benefit from incorporating more red cabbage into their meals. Further research into the mechanisms behind differences in red and green cabbage could inform breeding programs, enhancing nutritional traits for agricultural and dietary purposes.

plant biology↗