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PubMed2026

Coarse-grained resource allocation modeling for decoding and rewiring microbial metabolism.

Microbial metabolism is a complex, emergent system driven by the coordinated interplay of intricate and dynamic molecular processes. To elucidate cellular behavior and enable biotechnological applications, quantitative models that address the inherent complexity of metabolism have been developed from a resource allocation perspective. Here, we synthesize recent advances in coarse-grained resource allocation frameworks and their applications in understanding microbial physiology and guiding gene circuit design. These frameworks reveal global regulatory constraints and predict cellular adaptation to nutrient and environmental changes. In addition, they enable the quantification of metabolic costs, the dissection of circuit-host interactions, and the development of strategies for burden mitigation. Collectively, these modeling frameworks provide a powerful platform for uncovering quantitative principles of microbial growth and engineering robust synthetic biological systems.

coarse-grained modeling↗

PubMed2024

Variable resource allocation pattern, biased sex-ratio, and extent of sexual dimorphism in subdioecious Hippophae rhamnoides.

Evolutionary maintenance of dioecy is a complex phenomenon and varies by species and underlying pathways. Also, different sexes may exhibit variable resource allocation (RA) patterns among the vegetative and reproductive functions. Such differences are reflected in the extent of sexual dimorphism. Though rarely pursued, investigation on plant species harbouring intermediate sexual phenotypes may reveal useful information on the strategy pertaining to sex-ratios and evolutionary pathways. We studied H. rhamnoides ssp. turkestanica, a subdioecious species with polygamomonoecious (PGM) plants, in western Himalaya. The species naturally inhabits a wide range of habitats ranging from river deltas to hill slopes. These attributes of the species are conducive to test the influence of abiotic factors on sexual dimorphism, and RA strategy among different sexes. The study demonstrates sexual dimorphism in vegetative and reproductive traits. The sexual dimorphism index, aligned the traits like height, number of branches, flower production, and dry-weight of flowers with males while others including fresh-weight of leaves, number of thorns, fruit production were significantly associated with females. The difference in RA pattern is more pronounced in reproductive traits of the male and female plants, while in the PGM plants the traits overlap. In general, habitat conditions did not influence either the extent of sexual dimorphism or RA pattern. However, it seems to influence secondary sex-ratio as females show their significant association with soil moisture. Our findings on sexual dimorphism and RA pattern supports attributes of wind-pollination in the species. The observed extent of sexual dimorphism in the species reiterates limited genomic differences among the sexes and the ongoing evolution of dioecy via monoecy in the species. The dynamics of RA in the species appears to be independent of resource availability in the habitats as the species grows in a resource-limited and extreme environment.

Hippophae↗

PubMed2026

Turnip mosaic virus alters phosphorus metabolism and shoot-root allocation without resource competition.

Plant viruses affect production through symptom induction in host plants. These symptoms could partially arise from nutrient deprivation: The resource competition hypothesis posits that massive viral replication deprives hosts of essential nutrients, yet direct evidence for phosphorus (P) competition is lacking. Moreover, it is reported that biotic stresses can lead to alterations on P metabolism. Using a hydroponic system enabling separate analysis of shoots and roots in adult Arabidopsis thaliana plants, we investigated whether Turnip mosaic virus (TuMV) drawed significant P internal pools leading to P competition or altered P metabolism. TuMV genomic RNA represented < 0.3% of the P pool allocated to 18S rRNA, refuting the resource competition hypothesis. Instead, TuMV induced a marked shoot-to-root P redistribution: Shoot/Root Pi and Porg changed from 1.7 to 1.04 to 0.71 and 0.68, respectively. This altered partitioning correlated with organ-specific gene expression changes: high-affinity transporters PHT1; 4 and PHT1; 5 were co-induced in shoots, whereas immunity-related PHT1; 4 was uniquely repressed in roots. The senescence-associated gene SEN1 showed opposite regulation between organs (repressed in shoots, induced in roots), distinguishing virus-induced responses from canonical senescence. Multivariate analysis revealed that shoots and roots only partially share physiological and molecular responses to TuMV. The virus reprograms phosphorus metabolism through organ-specific changes, not through resource depletion, and roots act as a distinct hub integrating infection response, senescence, and nutrient dynamics. This study advances the understanding of growth-defense trade-offs in plant mineral nutrition and identifies new targets for maintaining crop productivity under biotic stress.

Arabidopsis↗

PubMed2026

Doublesex gene influences sex differentiation and embryonic development in predatory mite Phytoseiulus persimilis.

BACKGROUND: Phytoseiulus persimilis is an effective biocontrol agent characterized by paternal genome elimination (PGE), an unusual reproductive system in which males eliminate the paternal genome during embryogenesis. However, the molecular mechanism underlying sex determination and reproductive regulation in this species remain poorly understood. RESULTS: Transcriptome-based analyses identified two doublesex (dsx) homologs, Ppdsx1 and Ppdsx2, as candidate regulators of reproduction. Weighted gene co-expression network analysis (WGCNA) assigned Ppdsx2 to a pre-mating-associated co-expression module enriched for reproductive and signaling pathways. Functional analyses revealed clear divergence between the two genes. RNA interference (RNAi) of Ppdsx1 reduced the proportion of female offspring, whereas RNAi of Ppdsx2 induced sex reversal, developmental abnormalities, and impaired egg viability. Yeast two-hybrid and glutathione S-transferase (GST) pull-down assays further demonstrated interactions between Dsx proteins and vitellogenin (Vg)-derived fragments identified from a complementary DNA (cDNA) library screen, suggesting a previously unrecognized connection between sex determination and reproductive nutrient allocation. CONCLUSIONS: Ppdsx1 contributes to maintenance of the female developmental pathway, whereas Ppdsx2 represents a strong candidate component of the PGE-associated sex-determination cascade. The observed Dsx-Vg fragment interaction suggests a potential link between reproductive developmental programs and nutrient allocation pathways. These findings provide new insights into the molecular basis of sex determination and reproductive regulation in phytoseiid mites and establish a foundation for future studies on the coupling of reproductive development and resource allocation. © 2026 Society of Chemical Industry.

Animals↗

PubMed2026

Global inequities in hepatitis B and C genomic surveillance revealed through an interactive data integration dashboard.

OBJECTIVES: To assess global disparities in hepatitis B virus (HBV) and hepatitis C virus (HCV) genomic surveillance and to develop an integrated platform that links genomic data with epidemiological burden. STUDY DESIGN: Retrospective observational analysis. METHODS: We reviewed existing viral genomic repositories to identify structural and analytical limitations. Subsequently, we integrated 10 996 HBV and 3533 HCV whole-genome sequences (WGS) from public databases with Global Burden of Disease (GBD) estimates to quantify inequities in genomic surveillance across countries and genotypes. Using these data, we developed the open-access Hepatitis Dashboard, incorporating >14 000 sequences from 141 countries with GBD metrics to evaluate representativeness and sequencing coverage relative to disease burden. RESULTS: Marked inequities in hepatitis genomic surveillance were identified. Despite increasing HBV- and HCV-associated mortality, virus sequence availability remains geographically and genotypically skewed-dominated by China and the United States, with substantial underrepresentation of HBV genotype E and HCV genotypes 5 and 8. Many high-endemic countries in Africa and the Western Pacific remain severely undersampled. We detected circulating antiviral drug-resistance mutations and developed a burden-adjusted sequencing coverage metric, revealing that several high-burden countries, including China, Nigeria and India, are among the least represented in global genomic datasets. Projections to 2030 indicate that neither HBV nor HCV are currently on track to meet WHO elimination targets. CONCLUSIONS: The Hepatitis Dashboard provides an integrated, continuously updated resource that links genomic and epidemiological data to quantify and visualise global surveillance gaps. This analysis highlights a critical disconnect between sequencing efforts and public health needs, which may limit the effectiveness of surveillance-informed strategies to support progress toward WHO 2030 elimination goals. By enabling burden-adjusted prioritisation and longitudinal tracking of genomic coverage, the platform supports evidence-based sampling strategies, equitable resource allocation, and monitoring of global progress toward hepatitis elimination.

Humans↗

PubMed2025

ImmunoTar-integrative prioritization of cell surface targets for cancer immunotherapy.

MOTIVATION: Cancer remains a leading cause of mortality globally. Recent improvements in survival have been facilitated by the development of targeted and less toxic immunotherapies, such as chimeric antigen receptor (CAR)-T cells and antibody-drug conjugates (ADCs). These therapies, effective in treating both pediatric and adult patients with solid and hematological malignancies, rely on the identification of cancer-specific surface protein targets. While technologies like RNA sequencing and proteomics exist to survey these targets, identifying optimal targets for immunotherapies remains a challenge in the field. RESULTS: To address this challenge, we developed ImmunoTar, a novel computational tool designed to systematically prioritize candidate immunotherapeutic targets. ImmunoTar integrates user-provided RNA-sequencing or proteomics data with quantitative features from multiple public databases, selected based on predefined criteria, to generate a score representing the gene's suitability as an immunotherapeutic target. We validated ImmunoTar using three distinct cancer datasets, demonstrating its effectiveness in identifying both known and novel targets across various cancer phenotypes. By compiling diverse data into a unified platform, ImmunoTar enables comprehensive evaluation of surface proteins, streamlining target identification and empowering researchers to efficiently allocate resources, thereby accelerating the development of effective cancer immunotherapies. AVAILABILITY AND IMPLEMENTATION: Code and data to run and test ImmunoTar are available at https://github.com/sacanlab/immunotar.

Humans↗

PubMed2026

Metagenomic next-generation sequencing for tuberculosis diagnosis: enhanced performance and cost-effectiveness.

UNLABELLED: Metagenomic next-generation sequencing (mNGS) is a promising tool for diagnosing challenging infections like tuberculosis (TB). However, previous studies largely focused on case-specific application of mNGS in TB diagnosis. Thus, we conducted a retrospective observational study to first systematically evaluate the diagnostic performance and cost-effectiveness of mNGS for TB diagnosis. We retrieved a total of 16,776 results of the seven TB diagnostic assays, including mNGS, tuberculosis IgG antibody, TB interferon-γ release assay (TB-IGRA), TB-DNA, Xpert MTB/RIF (Xpert), culture, and acid-fast bacilli staining (AFS) from 3,757 participants with suspected TB infection at Sichuan Provincial People's Hospital from September 2021 to July 2024. Diagnostic metrics were compared against a composite reference standard. Microbial composition and a cost-utility analysis were performed. Among seven TB assays studied, the World Health Organization (WHO)-recommended assays AFS, culture, and Xpert, as well as TB-IGRA, were requested most frequently for TB diagnosis, whereas mNGS ranked last. mNGS demonstrated the highest specificity (100%), accuracy (72.3%), and area under the curve (AUC) (0.795). Its sensitivity in bronchoalveolar lavage fluid and tissue was 71.0% and 72.7%, respectively. Sequential use of mNGS after initial WHO-recommended tests (Xpert/Culture/AFS) significantly improved diagnostic performance (sensitivity, 70.4%; AUC, 0.823). Microbial analysis associated Candida albicans with TB. Cost-utility analysis showed sequential mNGS became cost-effective at higher willingness-to-pay thresholds (>200,000 RMB per correct diagnosis). mNGS offers superior specificity for TB diagnosis. A sequential strategy applying mNGS to conventional-test-negative cases provides enhanced diagnostic performance and is cost-effective at higher healthcare investment values, supporting its utility for diagnostically challenging TB. IMPORTANCE: This study systematically assesses the diagnostic performance and cost utility of metagenomic next-generation sequencing (mNGS) for tuberculosis (TB) in a large real-world cohort of 3,757 suspected patients, comparing it against six conventional assays (tuberculosis IgG antibody, TB interferon-γ release assay, TB-DNA, Xpert, culture, and acid-fast bacilli staining). mNGS demonstrated the highest specificity (100%), accuracy (72.3%), and area under the curve (AUC) (0.795), with sensitivities of 71.0% in bronchoalveolar lavage fluid and 72.7% in tissue. Notably, sequential use of mNGS after the World Health Organization-recommended tests significantly improved sensitivity to 70.4% and AUC to 0.823. Candida albicans showed significant differences among the three groups. The sequential mNGS strategy was cost-effective compared with no mNGS, and its cost-effectiveness increased with a rising willingness-to-pay threshold. Overall, these results highlight mNGS as a valuable supplementary tool for challenging TB cases, especially when conventional tests are inconclusive, and provide strong evidence for integrating it into diagnostic algorithms to optimize clinical decision-making and resource allocation.

Adult↗

PubMed2026

Multigene testing to guide clinical adjuvant decisions in breast cancer: An overview focused on the assessment of the quality of evidence with the grading of recommendations assessment, development and evaluation (GRADE) approach.

Multigene tests have emerged as valuable tools in guiding adjuvant chemotherapy decisions for patients with ER-positive/HER2-negative early breast cancer. This study applied the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach to assess the quality of evidence supporting the clinical utility of these tests. We focused on OncotypeDX® and MammaPrint®, the two tests evaluated in prospective randomized trials. The analysis was structured around the clinical question of whether these tests should be recommended for patients with ER-positive, HER2-negative, lymph node-negative or up to 3 lymph nodes-positive invasive breast cancer to guide adjuvant chemotherapy decisions. Our findings reveal that OncotypeDX® demonstrates high clinical utility in sparing chemotherapy for older/postmenopausal patients, with convincing quality of evidence for both node-negative and node-positive patients. The clinical utility of MammaPrint® appears more controversial, with conflicting results between node-negative and node-positive patients. A particularly critical aspect remains the clinical usefulness of these tests in younger/premenopausal women, where the benefit of adjuvant chemotherapy was shown but with potential biases in the study designs. Despite the established role of multigene tests and their availability in Italy since 2021, their uptake in clinical practice remains suboptimal. This formal appraisal of the clinical utility of genomic tests, particularly OncotypeDX®, aims to reinforce their fundamental role in personalizing adjuvant treatment decisions and optimizing resource allocation. The study underscores the importance of these tests in sparing unnecessary chemotherapy toxicities and costs, while emphasizing the need for further research to address remaining uncertainties, especially in younger patient populations.

Humans↗

PubMed2026

Integrated landscape of salivary metagenome and multi-biofluid metabolome characterizes a microbial-metabolic axis in upper gastrointestinal cancer progression.

BACKGROUND: Upper gastrointestinal cancer (UGIC) imposes a major global health burden, yet the stage-specific molecular changes along the microbial-metabolic axis remain limited understood. We aimed to delineate this molecular landscape across UGIC progression and evaluate its potential as non-invasive methods for precision screening. RESULTS: Derived from a multi-center population-based UGIC screening program, we enrolled 420 individuals, stratified into normal, low-grade intraepithelial neoplasia (LGIN), high-grade intraepithelial neoplasia (HGIN), and UGIC (n = 105 per group). Integrated salivary metagenomics and paired salivary/plasma metabolomics were performed to capture local and systemic dysregulation. We uncovered distinct stage-specific divergence during UGIC progression: profound remodeling of the salivary microbiota (104 differential species) and salivary metabolomics (80 differential metabolites) initiated early at the LGIN stage, whereas plasma metabolic dysregulation (40 differential metabolites) peaked significantly later at the HGIN stage. Integrative analysis revealed salivary microbiota related more closely with salivary metabolome than plasma metabolome. Moreover, statistical evidence suggested that dysbiotic salivary microbiota was associated with altered lysine- and tryptophan-related catabolic pathways converging on Acetyl-CoA-related metabolic nodes, supporting a potential metabolic mechanism in precancerous lesions. Finally, the discriminative model integrating metagenomic and metabolomic markers demonstrated promising diagnostic performance in distinguishing these precancerous lesions (LGIN: area under the curve [AUC] = 0.83; HGIN: AUC = 0.77) and UGIC (AUC = 0.76) from normal. CONCLUSION: This study characterizes a stage-specific microbial-metabolic axis that facilitates the comprehensive understanding of UGIC pathogenesis. These multi-biofluid signatures offer a promising non-invasive triage strategy for detecting precancerous lesions and optimizing endoscopic resource allocation. Video Abstract.

Female↗

PubMed2025

Urban mental health: a position paper of the European psychiatric association.

BACKGROUND: Urbanization, the shift of a growing population into urban areas, is shaping global development across infrastructure, health, and sustainability. Although it brings economic growth, innovation, and improved access to services, it may also impact mental health. METHODS: The present article was prepared on behalf of the European Psychiatric Association and explores the complexity of associations between urbanization and mental health, highlighting both potential risks and opportunities for improvement. RESULTS: Urban growth often leads to increased population density, social fragmentation, and environmental stressors, including noise, pollution, and reduced green spaces, all of which might account for worsening mental health. Urban residents might be at risk of various mental disorders due to these stressors, accompanied by the risk of social disconnection. Moreover, socioeconomic disparities in urban settings can lead to unequal healthcare access, further contributing to these challenges. However, urbanization also offers unique opportunities to improve mental health through better resource allocation, innovative healthcare solutions, and community-building initiatives. Indeed, cities might serve as areas for mental health promotion by integrating mental health services into primary care, utilizing digital health technologies, and fostering environments that promote social interactions and well-being. Urban planning that prioritizes green spaces, safe housing, and accessible public transportation holds the potential to mitigate some risks related to urban living. CONCLUSIONS: While urbanization presents significant challenges to mental health, it also provides grounds for transformative interventions. Addressing the mental health needs of urban populations requires a multifaceted approach that includes policy reform, community engagement, and sustainable urban planning.

Humans↗

PubMed2026

Mapping the de-implementation of traditional diagnostic tests in pediatric acute lymphoblastic leukemia.

INTRODUCTION: Advances in cancer diagnostics raise questions about when and how to de-implement traditional approaches; however, these processes remain poorly described. At St. Jude Children's Research Hospital (SJCRH), routine conventional cytogenetics for pediatric acute lymphoblastic leukemia (ALL) diagnosis was de-implemented in 2018 following adoption of clinical genomics. This study aimed to map this process to inform future diagnostic de-implementation initiatives. METHODS: Interviews were conducted with SJCRH staff involved or impacted by cytogenetics de-implementation. Data were analyzed using thematic and rapid qualitative analysis informed by the Consolidated Framework for Implementation Research. Member-checking was used to verify and refine process maps, which were subsequently reviewed by an external expert panel, representing diverse settings, through focus group discussions. RESULTS: Thirteen SJCRH clinicians participated. De-implementation was described as successful, with no negative impact on patient outcomes. Decision-making began with internal correlation studies that demonstrated superior diagnostic performance of clinical genomics. De-implementation was viewed as a natural evolution that improved molecular classification, resource allocation, and workflow efficiency. Perceived risks included loss of cytogenetics competency, delayed turnaround time, and career insecurity, all addressed institutionally. Lessons learned highlighted the importance of deliberate discussion about logic and evidence supporting de-implementation. Fifteen external experts offered suggestions to improve process map generalizability, highlighting institutional- and system-level considerations. CONCLUSION: De-implementation of cytogenetics in ALL in favor of clinical genomics was successful at SJCRH. This study offers an example of diagnostic de-implementation in cancer care and proposes a structured approach to guide future efforts. De-implementation should be considered alongside introduction of novel diagnostic approaches.

cancer diagnostics↗

PubMed2025

Yeast growth is controlled by the proportional scaling of mRNA and ribosome concentrations.

Despite growth being fundamental to all aspects of cell biology, we do not yet know its organizing principles in eukaryotic cells. Classic models derived from the bacteria E. coli posit that protein-synthesis rates are set by mass-action collisions between charged tRNAs produced by metabolic enzymes and mRNA-bound ribosomes. These models show that faster growth is achieved by simultaneously raising both ribosome content and peptide elongation speed. Here, we test if these models are valid for eukaryotes by combining single-molecule tracking, spike-in RNA sequencing, and proteomics in 15 carbon- and nitrogen-limited conditions using the budding yeast S. cerevisiae. Ribosome concentration increases linearly with growth rate, as in bacteria, but the peptide elongation speed remains constant (~9 amino acids/s) and charged tRNAs are not limiting. Total mRNA concentration rises in direct proportion to ribosomes, driven by enhanced RNA polymerase II occupancy of the genome. We show that a simple kinetic model of mRNA-ribosome binding predicts both the fraction of active ribosomes, the growth rate, and responses to transcriptional perturbations. Yeast accelerate growth by coordinately and proportionally co-up-regulating total mRNA and ribosome concentrations, not by speeding elongation. Taken together, our work establishes a new framework for eukaryotic growth control and resource allocation.

Journal Article↗

PubMed2026

Membrane and proteome allocation constraints in Escherichia coli models during overflow metabolism.

The allocation of finite cellular resources is a fundamental principle that dictates microbial metabolic strategies and gives rise to complex phenomena, such as overflow metabolism, characterized by the production of respiro-fermentative by-products, including acetate, during rapid growth. Although proteome-constrained models have successfully predicted overflow metabolism in Escherichia coli, they often overlook the distinct biophysical and energetic costs associated with protein localization. The cellular membrane, in particular, represents a critical and constrained compartment where competition for space and synthesis machinery can create significant metabolic bottlenecks. To investigate this, we developed the membrane-associated constrained flux balance analysis (MAFBA), a scalable, genome-scale metabolic model that introduces a tunable constraint on the total protein mass allocated to the cellular membrane. Our model demonstrates that the overall and membrane-associated proteome allocation constraints interact to improve the accuracy of predicting the onset of overflow metabolism. It mechanistically reveals that at high growth rates, competition for limited membrane allocation forces a trade-off between growth-essential functions and respiratory capacity, leading to acetate production. Furthermore, MAFBA quantitatively explains the widely observed experimental phenomenon that expressing heterologous membrane proteins imposes a significantly higher metabolic burden than expressing cytosolic proteins. This study establishes membrane resource allocation as a key constraint governing bacterial physiology, acting in concert with overall proteome limitations. The resulting MAFBA framework provides a powerful and accessible tool for synthetic biology and metabolic engineering, enabling the prediction of metabolic costs associated with expressing membrane-bound proteins and guiding strain design strategies, holding promise for applications in bioproduction and metabolic engineering.

Escherichia coli↗

PubMed2025

Inferring metabolic objectives and trade-offs in single cells during embryogenesis.

While proliferating cells optimize their metabolism to produce biomass, the metabolic objectives of cells that perform non-proliferative tasks are unclear. The opposing requirements for optimizing each objective result in a trade-off that forces single cells to prioritize their metabolic needs and optimally allocate limited resources. Here, we present single-cell optimization objective and trade-off inference (SCOOTI), which infers metabolic objectives and trade-offs in biological systems by integrating bulk and single-cell omics data, using metabolic modeling and machine learning. We validated SCOOTI by identifying essential genes from CRISPR-Cas9 screens in embryonic stem cells, and by inferring the metabolic objectives of quiescent cells, during different cell-cycle phases. Applying this to embryonic cell states, we observed a decrease in metabolic entropy upon development. We further uncovered a trade-off between glutathione and biosynthetic precursors in one-cell zygote, two-cell embryo, and blastocyst cells, potentially representing a trade-off between pluripotency and proliferation. A record of this paper's transparent peer review process is included in the supplemental information.

Single-Cell Analysis↗

PubMed2025

Trade-off between antibacterial immune defense and oogenesis progression in female Drosophila melanogaster.

Trade-offs between reproduction and immunity are common in animals, potentially due to preferential allocation of limiting resources. In Drosophila melanogaster, mating stimulates egg production but also triggers a rapid and persistent decrease in female immune defense. Proteins essential for both processes are produced in fat body tissue, which may result in competition for cellular resources that could drive a functional trade-off between reproduction and immune defense. We predicted that arrest of oogenesis prior to egg provisioning would alleviate postmating immune suppression because cellular stress would be relieved, but that postmating immune suppression would be observed in genotypes that fully provision eggs even if fertility is compromised. In the present study, we test these predictions by evaluating postmating immune competence in mated D. melanogaster mutants that arrest oogenesis either prior to, or subsequent to, vitellogenesis. Consistent with our prediction, we find that mated female immune defense is maintained when egg development is arrested prior to vitellogenesis. We find that progression through the vitellogenic stages of oogenesis results in postmating immune suppression, except in the case of a mutant with an egg-retention phenotype, where we infer that the failure to lay eggs results in feedback that inhibits subsequent egg development. We additionally show that elimination of yolk protein synthesis in the fat body and follicle cells of the ovary partially restores female immune capacity. Nevertheless, females that lack yolk protein genes still experience partially reduced immune capacity after mating, suggesting that other reproductive demands also suppress immune defense.

Animals↗

PubMed2024

Genetic determinants of SARS-CoV-2 and the clinical outcome of COVID-19 in Southern Bangladesh.

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic has had a severe impact on population health. The genetic determinants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in southern Bangladesh are not well understood. METHODS: This study aimed to determine the genomic variation in SARS-CoV-2 genomes that have evolved over 2 years of the pandemic in southern Bangladesh and their association with disease outcomes and virulence of this virus. We investigated demographic variables, disease outcomes of COVID-19 patients and genomic features of SARS-CoV-2. RESULTS: We observed that the disease severity was significantly higher in adults (85.3%) than in children (14.7%), because the expression of angiotensin-converting enzyme-2 (ACE-2) diminishes with ageing that causes differences in innate and adaptive immunity. The clade GK (n = 66) was remarkable between June 2021 and January 2022. Because of the mutation burden, another clade, GRA started a newly separated clustering in December 2021. The burden was significantly higher in GRA (1.5-fold) highlighted in mild symptoms of COVID-19 patients than in other clades (GH, GK, and GR). Mutations were accumulated mainly in S (22.15 mutations per segment) and ORF1ab segments. Missense (67.5%) and synonymous (18.31%) mutations were highly noticed in adult patients with mild cases rather than severe cases, especially in ORF1ab segments. Moreover, we observed many unique mutations in S protein in mild cases compared to severe, and homology modeling revealed that those might cause more folding in the protein's alpha helix and beta sheets. CONCLUSION: Our study identifies some risk factors such as age comorbidities (diabetes, hypertension, and renal disease) that are associated with severe COVID-19, providing valuable insight regarding prioritizing vaccination for high-risk individuals and allocating health care and resources. The findings of this work outlined the knowledge and mutational basis of SARS-CoV-2 for the next treatment steps. Further studies are needed to confirm the effects of structural and functional proteins of SARS-CoV-2 in detail for monitoring the emergence of new variants in future.

Adult↗

PubMed2026

A note on a generalized single step theory for any number of hierarchical genomic matrices.

BACKGROUND: The Single Step algorithm allows combining information from genotyped and un-genotyped individuals, provided they are connected by a pedigree. However, current single step theory is limited to a single list of markers. RESULTS: We present a generalized single step (GSS) method that can accommodate any number of hierarchical molecular datasets (e.g. sequence, high and low density arrays) and pedigree, avoiding imputation. We prove that a similar efficient inversion algorithm exists. The method is recursive, starting with the highest marker density scenario. We illustrate the method with simulation and show that GSS can increase predictive accuracy compared to standard single step. R code is provided so that custom scenarios can be easily compared, either with simulated or real data. CONCLUSION: The method developed generalizes extant single step theory to any number of hierarchical molecular relationship matrices, broadening the scenarios where single step can be applied. A topic of particular interest can be ecology field data or human populations where pedigree is not available, but where samples sequenced and genotyped at different densities can exist. GSS can also be a useful tool to optimize allocation of genotyping and / or sequencing resources.

Algorithms↗

PubMed2026

Implications of proteome allocation constraints for understanding interbacterial antagonism.

Bacteria live in dense communities where competition influences the composition and, therefore, the function of these communities. Beyond competing for resources, bacteria engage in antagonism by deploying a range of molecular weapon systems to inhibit and kill other bacteria. Investing in antagonism is expected to incur a fitness trade-off, but the nature of this trade-off at the level of molecular physiology remains underexplained. Applying recent advances about the physiological constraints faced by bacterial cells may help us better understand existing studies and design new investigations into interbacterial antagonism. Bacterial cells face two important constraints: a finite amount of protein and a maximum translation speed for ribosomes. As a result, the only way for a cell to grow faster is to allocate more of its finite proteome to synthesizing ribosomes. A cell choosing to attack competitors must therefore allocate some of its limited proteome budget to antagonistic proteins instead of other functions. Conversely, being attacked and resisting the effects of such attacks also require an investment of proteomic resources. The extent to which proteome allocation constraints influence bacterial physiology is not fully understood; consequently, how these constraints influence interbacterial antagonism has not been investigated. Here, I will discuss how proteome allocation constraints can re-contextualize our existing understanding of the costs of both deploying and resisting attacks and how investigation of these constraints may further our understanding of interbacterial antagonism.

Proteome↗