Large-scale gene function analysis with the PANTHER classification system

Mapping taste and flavour traits to genetic markers in lettuce Lactuca sativa

Lettuce is the most highly consumed raw leafy vegetable crop eaten worldwide, making it nutritionally important in spite of its comparatively low nutrient density in relation to other vegetables. However, the perception of bitterness caused by high levels of sesquiterpenoid lactones and comparatively low levels of sweet tasting sugars limits palatability. To assess variation in nutritional and taste-related metabolites we assessed 104 members of a Lactuca sativa cv. Salinas x L. serriola (accession UC96US23) mapping population. Plants were grown in three distinct environments, and untargeted NMR and HPLC were used as a rapid chemotyping method, from which 63 unique Quantitative Trait Loci (QTL) were identified. We were able to identify putative regulatory candidate genes underlying the QTL for fructose on linkage group 9, which accounted for up to 36 % of our population variation, and which was stable across all three growing environments; and for 15-p-hydroxyyphenylacetyllactucin-8-sulfate on linkage group 5 which has previously been identified for its low bitterness, while retaining anti-herbivory field effects. We also identified a candidate gene for flavonoid 3',5'- hydroxylase underlying a polyphenol QTL on linkage group 5, and two further candidate genes in sugar biosynthesis on linkage groups 2 and 5. Collectively these candidate genes and their associated markers can inform a route for plant breeders to improve the palatability and nutritional value of lettuce in their breeding programmes.

Resistance and aerobic training increases genome-wide DNA methylation in women with polycystic ovary syndrome

Physical activity is a first-line treatment for polycystic ovary syndrome (PCOS). Resistance or aerobic exercise improves metabolic complications, reproductive outcomes, and quality of life in PCOS. DNA methylation reprogramming during exercise may be the major modifier behind these changes. We sought to evaluate genome-wide DNA methylation changes after supervised resistance and aerobic exercise in women with PCOS. Exercises were performed in 56 women with PCOS (resistance, n = 30; aerobic, n = 26), for 16 weeks (wks), three times per week, in 50-minute to one-hour sessions. Anthropometric indices and hormonal and metabolic parameters were measured before and after training. Genome-wide leukocyte DNA methylation was analysed by Infinium Human MethylationEPIC 850K BeadChip microarrays (Illumina). Both resistance and aerobic exercise improved anthropometric indices, metabolic dysfunction, and hyperandrogenism in PCOS after the training programme, but no differences were observed between the two exercises. Resistance and aerobic exercise increased genome-wide DNA methylation, although resistance changed every category in the CpG island context (islands, shores, shelve, and open sea), whereas aerobic exercise altered CpG shores and the open sea. Using a stringent FDR (>40), 6 significantly differentially methylated regions (DMRs) were observed in the resistance exercise cohort and 14 DRMs in the aerobic cohort, all of which were hypermethylated. The increase in genome-wide DNA methylation may be related to the metabolic and hormonal changes observed in PCOS after resistance and aerobic exercise. Since the mammalian genome is hypermethylated globally to prevent genomic instability and ageing, resistance and aerobic exercise may promote health and longevity through environmentally induced epigenetic changes.

Knockdown of cullin 3 inhibits progressive phenotypes and increases chemosensitivity in cholangiocarcinoma cells

Cholangiocarcinoma (CCA) is an extremely aggressive malignancy arising from the epithelial cells lining the bile ducts. It presents a substantial global health issue, with the highest incidence rates, ranging from 40‑100 cases/100,000 individuals, found in Southeast Asia, where liver fluke infection is endemic. In Europe and America, incidence rates range from 0.4‑2 cases/100,000 individuals. Globally, mortality rates range from 0.2‑2 deaths/100,000 person‑years and are increasing in most countries. Chemotherapy is the primary treatment for advanced CCA due to limited options from late‑stage diagnosis, but its efficacy is hindered by drug‑resistant phenotypes. In a previous study, proteomics analysis of drug‑resistant CCA cell lines (KKU‑213A‑FR and KKU‑213A‑GR) and the parental KKU‑213A line identified cullin 3 (Cul3) as markedly overexpressed in drug‑resistant cells. Cul3, a scaffold protein within CUL3‑RING ubiquitin ligase complexes, is crucial for ubiquitination and proteasome degradation, yet its role in drug‑resistant CCA remains to be elucidated. The present study aimed to elucidate the role of Cul3 in drug‑resistant CCA cell lines. Reverse transcription‑quantitative PCR and western blot analyses confirmed significantly elevated Cul3 mRNA and protein levels in drug‑resistant cell lines compared with the parental control. Short interfering RNA‑mediated Cul3 knockdown sensitized cells to 5‑fluorouracil and gemcitabine and inhibited cell proliferation, colony formation, migration and invasion. In addition, Cul3 knockdown induced G0/G1 cell cycle arrest and suppressed key cell cycle regulatory proteins, cyclin D, cyclin‑dependent kinase (CDK)4 and CDK6. Bioinformatics analysis of CCA patient samples using The Cancer Genome Atlas data revealed Cul3 upregulation in CCA tissues compared with normal bile duct tissues. STRING analysis of upregulated proteins in drug‑resistant CCA cell lines identified a highly interactive Cul3 network, including COMM Domain Containing 3, Ariadne RBR E3 ubiquitin protein ligase 1, Egl nine homolog 1, Proteasome 26S Subunit Non‑ATPase 13, DExH‑box helicase 9 and small nuclear ribonucleoprotein polypeptide G, which showed a positive correlation with Cul3 in CCA tissues. Knocking down Cul3 significantly suppressed the mRNA expression of these genes, suggesting that Cul3 may act as an upstream regulator of them. Gene Ontology analysis revealed that the majority of these genes were categorized under binding function, metabolic process, cellular anatomical entity, protein‑containing complex and protein‑modifying enzyme. Taken together, these findings highlighted the biological and clinical significance of Cul3 in drug resistance and progression of CCA.

Statistical approaches applicable in managing OMICS data: Urinary proteomics as exemplary case

With urinary proteomics profiling (UPP) as exemplary omics technology, this review describes a workflow for the analysis of omics data in large study populations. The proposed workflow includes: (i) planning omics studies and sample size considerations; (ii) preparing the data for analysis; (iii) preprocessing the UPP data; (iv) the basic statistical steps required for data curation; (v) the selection of covariables; (vi) relating continuously distributed or categorical outcomes to a series of single markers (e.g., sequenced urinary peptide fragments identifying the parental proteins); (vii) showing the added diagnostic or prognostic value of the UPP markers over and beyond classical risk factors, and (viii) pathway analysis to identify targets for personalized intervention in disease prevention or treatment. Additionally, two short sections respectively address multiomics studies and machine learning. In conclusion, the analysis of adverse health outcomes in relation to omics biomarkers rests on the same statistical principle as any other data collected in large population or patient cohorts. The large number of biomarkers, which have to be considered simultaneously requires planning ahead how the study database will be structured and curated, imported in statistical software packages, analysis results will be triaged for clinical relevance, and presented.

Next-generation mapping of the salicylic acid signaling hub and transcriptional cascade

For over 60 years, salicylic acid (SA) has been known as a plant immune signal required for basal and systemic acquired resistance. SA activates these immune responses by reprogramming ∼20% of the transcriptome through NPR1. However, components in the NPR1 signaling hub, which appears as nuclear condensates, and the NPR1 signaling cascade have remained elusive due to difficulties in studying this transcriptional cofactor, whose chromatin association is indirect and likely transient. To overcome this challenge, we applied TurboID to divulge the NPR1 proxiome, which detected almost all known NPR1 interactors as well as new components of transcription-related complexes. Testing of new components showed that chromatin remodeling and histone demethylation contribute to SA-induced resistance. Globally, the NPR1 proxiome has a striking similarity to the proxiome of GBPL3 that is involved in SA synthesis, except for associated transcription factors (TFs), suggesting that common regulatory modules are recruited to reprogram specific transcriptomes by transcriptional cofactors, like NPR1, through binding to unique TFs. Stepwise green fluorescent protein-tagged factor cleavage under target and release using nuclease (greenCUT&RUN) analyses showed that, upon SA induction, NPR1 initiates the transcriptional cascade primarily through association with TGACG-binding TFs to induce expression of secondary TFs, predominantly WRKYs. Further, WRKY54 and WRKY70 were identified to play a major role in inducing immune-output genes without interacting with NPR1 at the chromatin. Moreover, loss of condensate formation function of NPR1 decreases its chromatin association and transcriptional activity, indicating the importance of condensates in organizing the NPR1 signaling hub and initiating the transcriptional cascade. Collectively, this study demonstrates how combinatorial applications of TurboID and stepwise greenCUT&RUN transcend traditional genetic methods to globally map signaling hubs and transcriptional cascades for in-depth explorations.

In vivo detection of endogenous toxic phenolic compounds of intestine

Phenol and p-cresol are two common toxic small molecules related to various diseases. Existing reports confirmed that high L-tyrosine in the daily diet can increase the concentration of phenolic compounds in blood and urine. L-tyrosine is a common component of protein-rich foods. Some anaerobic bacteria in the gut can convert non-toxic l-tyrosine into these two toxic phenolic compounds, phenol and p-cresol. Existing methods have been constructed for measuring the concentration of phenolic compound in feces. However, there is still a lack of direct visual evidence to measure the phenolic compounds in the intestine. In this study, we aimed to construct a whole-cell biosensor for phenolic compounds detection based on the dmpR, the regulator from the phenol metabolism cluster. The commensal bacterium Citrobacter amalonaticus PS01 was selected and used as the chassis. Compared with the biosensor based on ECN1917, the biosensor PS01[dmpR] could better implant into the mouse gut through gavage and showed a higher sensitive to phenolic compound. And the concentration of phenolic compounds in the intestines could be observed with the help of in vivo imaging system using PS01[dmpR]. This paper demonstrated endogenous phenol synthesis in the gut and the strategy of using commensal bacteria to construct whole-cell biosensors for detecting small molecule compounds in the intestines.

Identification of DNA methylation markers for age and Bovine Respiratory Disease in dairy cattle: A pilot study based on Reduced Representation Bisulfite Sequencing

Methylation profiles of animals are known to differ by age and disease status. Bovine respiratory disease (BRD), a complex infectious disease, primarily affects calves and has significant impact on animal welfare and the cattle industry, due to production losses, increased veterinary costs as well as animal losses. BRD susceptibility is multifactorial, influenced by both environmental and genetic factors. We have performed a pilot study to investigate the epigenetic profile of BRD susceptibility in six calves (three healthy versus three diagnosed with BRD) and age-related methylation differences between healthy calves and adult dairy cows (three calves versus four adult cows) using Reduced Representation Bisulfite Sequencing (RRBS). We identified 2537 genes within differentially methylated regions between calves and adults. Functional analysis revealed enrichment of developmental pathways including cell fate commitment and tissue morphogenesis. Between healthy and BRD affected calves, 964 genes were identified within differentially methylated regions. Immune and vasculature regulatory pathways were enriched and key candidates in BRD susceptibility involved in complement cascade regulation, vasoconstriction and respiratory cilia structure and function were identified. Further studies with a greater sample size are needed to validate these findings and formulate integration into breeding programmes aiming to increase animal longevity and disease resistance.

Tissue Inhibitor of Metalloproteinase 3 (TIMP3) mutations increase glycolytic activity and dysregulate glutamine metabolism in RPE cells

OBJECTIVES

Mutations in Tissue Inhibitor of Metalloproteinases 3 (TIMP3) cause Sorsby's Fundus Dystrophy (SFD), a dominantly inherited, rare form of macular degeneration that results in vision loss. TIMP3 is synthesized primarily by retinal pigment epithelial (RPE) cells, which constitute the outer blood-retinal barrier. One major function of RPE is the synthesis and transport of vital nutrients, such as glucose, to the retina. Recently, metabolic dysfunction in RPE cells has emerged as an important contributing factor in retinal degenerations. We set out to determine if RPE metabolic dysfunction was contributing to SFD pathogenesis.

METHODS

Quantitative proteomics was conducted on RPE of mice expressing the S179C variant of TIMP3, known to be causative of SFD in humans. Proteins found to be differentially expressed (P < 0.05) were analyzed using statistical overrepresentation analysis to determine enriched pathways, processes, and protein classes using g:profiler and PANTHER Gene Ontology. We examined the effects of mutant TIMP3 on RPE metabolism using human ARPE-19 cells expressing mutant S179C TIMP3 and patient-derived induced pluripotent stem cell-derived RPE (iRPE) carrying the S204C TIMP3 mutation. RPE metabolism was directly probed using isotopic tracing coupled with GC/MS analysis. Steady state [U-13C6] glucose isotopic tracing was preliminarily conducted on S179C ARPE-19 followed by [U-13C6] glucose and [U-13C5] glutamine isotopic tracing in SFD iRPE cells.

RESULTS

Quantitative proteomics and enrichment analysis conducted on RPE of mice expressing mutant S179C TIMP3 identified differentially expressed proteins that were enriched for metabolism-related pathways and processes. Notably these results highlighted dysregulated glycolysis and glucose metabolism. Stable isotope tracing experiments with [U-13C6] glucose demonstrated enhanced glucose utilization and glycolytic activity in S179C TIMP3 APRE-19 cells. Similarly, [U-13C6] glucose tracing in SFD iRPE revealed increased glucose contribution to glycolysis and the TCA cycle. Additionally, [U-13C5] glutamine tracing found evidence of altered malic enzyme activity.

CONCLUSIONS

This study provides important information on the dysregulation of RPE glucose metabolism in SFD and implicates a potential commonality with other retinal degenerative diseases, emphasizing RPE cellular metabolism as a therapeutic target.

Genomics 2 Proteins portal: a resource and discovery tool for linking genetic screening outputs to protein sequences and structures

Recent advances in AI-based methods have revolutionized the field of structural biology. Concomitantly, high-throughput sequencing and functional genomics have generated genetic variants at an unprecedented scale. However, efficient tools and resources are needed to link disparate data types-to 'map' variants onto protein structures, to better understand how the variation causes disease, and thereby design therapeutics. Here we present the Genomics 2 Proteins portal ( https://g2p.broadinstitute.org/ ): a human proteome-wide resource that maps 20,076,998 genetic variants onto 42,413 protein sequences and 77,923 structures, with a comprehensive set of structural and functional features. Additionally, the Genomics 2 Proteins portal allows users to interactively upload protein residue-wise annotations (for example, variants and scores) as well as the protein structure beyond databases to establish the connection between genomics to proteins. The portal serves as an easy-to-use discovery tool for researchers and scientists to hypothesize the structure-function relationship between natural or synthetic variations and their molecular phenotypes.

Exome sequencing of 20,979 individuals with epilepsy reveals shared and distinct ultra-rare genetic risk across disorder subtypes

Identifying genetic risk factors for highly heterogeneous disorders such as epilepsy remains challenging. Here we present, to our knowledge, the largest whole-exome sequencing study of epilepsy to date, with more than 54,000 human exomes, comprising 20,979 deeply phenotyped patients from multiple genetic ancestry groups with diverse epilepsy subtypes and 33,444 controls, to investigate rare variants that confer disease risk. These analyses implicate seven individual genes, three gene sets and four copy number variants at exome-wide significance. Genes encoding ion channels show strong association with multiple epilepsy subtypes, including epileptic encephalopathies and generalized and focal epilepsies, whereas most other gene discoveries are subtype specific, highlighting distinct genetic contributions to different epilepsies. Combining results from rare single-nucleotide/short insertion and deletion variants, copy number variants and common variants, we offer an expanded view of the genetic architecture of epilepsy, with growing evidence of convergence among different genetic risk loci on the same genes. Top candidate genes are enriched for roles in synaptic transmission and neuronal excitability, particularly postnatally and in the neocortex. We also identify shared rare variant risk between epilepsy and other neurodevelopmental disorders. Our data can be accessed via an interactive browser, hopefully facilitating diagnostic efforts and accelerating the development of follow-up studies.

Relevance of the regulation of the brain-placental axis to the nocturnal bottleneck of mammals

INTRODUCTION

Evolutionary theory suggests that the ancestors of all placental animals were nocturnal. Visual perceptive function of mammalian brain has evolved extensively, but nearly 70 % of today's mammals are still nocturnal. While placental influence on brain development is known, if placenta plays a role in the visual perceptive function of mammalian brain remains untested. The present study aims to test this hypothesis.

METHODS

In this study, single-nuclei RNA sequencing was performed to identify genes expressed in the pig placenta and fetal brain, and then compared with the orthologous genes expressed in the placenta and fetal brain cells of mouse. Differential gene expression analysis was performed to identify placental genes regulated differentially between nocturnal and diurnal animals. Phylogenetic modeling was performed to test correlated evolution between placenta type, and the nocturnal or diurnal activity among different mammals.

RESULTS

The results showed that genes differentially regulated in the fetal brain were related to visual perception whereas the placental genes were related to the nocturnal or diurnal activity in placental animals. Phylogenetic modeling of these genes in thirty-four diverse mammalian species showed evidence for evolutionary link between placenta and the nocturnal/diurnal activity in animals.

DISCUSSION

The findings of this study suggest that the placenta plays a role in the evolution of visual perceptive function of brain to shape the nocturnal or diurnal activity of placental animals.

Comparison of B-Cell Lupus and Lymphoma Using a Novel Immune Imbalance Transcriptomics Algorithm Reveals Potential Therapeutic Targets

BACKGROUND/OBJECTIVES

Systemic lupus erythematosus (lupus) and B-cell lymphoma (lymphoma) co-occur at higher-than-expected rates and primarily depend on B cells for their pathology. These observations implicate shared inflammation-related B cell molecular mechanisms as a potential cause of co-occurrence.

METHODS

We consequently implemented a novel Immune Imbalance Transcriptomics (IIT) algorithm and applied IIT to lupus, lymphoma, and healthy B cell RNA-sequencing (RNA-seq) data to find shared and contrasting mechanisms that are potential therapeutic targets.

RESULTS

We observed 7143 significantly dysregulated genes in both lupus and lymphoma. Of those genes, we found 5137 to have a significant immune imbalance, defined as a significant dysregulation by both diseases, as analyzed by IIT. Gene Ontology (GO) term and pathway enrichment of the IIT genes yielded immune-related "Neutrophil Degranulation" and "Adaptive Immune System", which validates that the IIT algorithm isolates biologically relevant genes in immunity and inflammation. We found that 344 IIT gene products are known targets for established and/or repurposed drugs. Among our results, we found 48 known and 296 novel lupus targets, along with 151 known and 193 novel lymphoma targets. Known disease drug targets in our IIT results further validate that IIT isolates genes with disease-relevant mechanisms.

CONCLUSIONS

We anticipate the IIT algorithm, together with the shared and contrasting gene mechanisms uncovered here, will contribute to the development of immune-related therapeutic options for lupus and lymphoma patients.

Extracellular vesicles released by Trypanosoma evansi: induction analysis and proteomics

Trypanosoma evansi is a unicellular protozoan responsible for causing a disease known as "surra," which is found in different regions of the world and primarily affects horses and camels. Few information is known about virulence factors released from the parasite within the animals. The organism can secrete extracellular vesicles (EVs), which transport a variety of molecules, including proteins. Before being considered exclusively as a means for eliminating unwanted substances, extracellular vesicles (EVs) have emerged as key players in intercellular communication, facilitating interactions between cells, host cells, and parasites, and even between parasites themselves. Thus, they may be used as potential biomarkers. This study aimed to assess the induction of EVs production by Ca+2, conduct a proteomic analysis of the EVs released by T. evansi, and identify epitopes that could serve as biomarkers. The findings indicated that Ca+2 is not an effective promoter of vesiculation in T. evansi. Furthermore, the proteomic analysis has identified multiple proteins that have been investigated as biomarkers or vaccine antigens, previously. A total of 442 proteins were identified, with 7 of them specifically recognizing 9 epitopes that are unique to T. evansi. At least one of these epitopes of TevSTIB805.9.11580 have been previously identified, which increases the possibility of further investigating its potential as a biomarker.

RNA-Seq Analysis Unraveling Novel Genes and Pathways Influencing Corneal Wound Healing

Purpose

Transdifferentiation of corneal fibroblasts to myofibroblasts in the stroma is a central mechanistic event in corneal wound healing. This study sought to characterize genes and pathways influencing transdifferentiation of human corneal fibroblasts (hCSFs) to human corneal myofibroblasts (hCMFs) using RNA sequencing (RNA-seq) to develop comprehensive mechanistic information and identify newer targets for corneal fibrosis management.

Methods

Primary hCSFs were derived from donor human corneas. hCMFs were generated by treating primary hCSFs with transforming growth factor β1 (TGFβ1; 5 ng/mL) for 72 hours under serum-free conditions. RNA was extracted using the RNeasy Plus Mini Kit and subjected to RNA-seq analysis after quality control testing. Differential gene expression, pathway enrichment, and protein-protein network analyses were performed using DESeq2, GSEA/PANTHER/Reactome, and Cytoscape/cytoHubba, respectively.

Results

RNA-seq analysis of hCMFs and hCSFs identified 3843 differentially expressed genes and transcripts (adjusted P < 0.05). The log(fold change) ≥ ±1.5 filter showed 816 upregulated and 739 downregulated genes between two cell types. Pathway enrichment analysis showed the highest normalized enrichment score for epithelial-to-mesenchymal transition (5.569), followed by mTORC1 signaling (2.949), angiogenesis (2.176), and TGFβ signaling (2.008). Protein-protein interaction network analysis identified the top 20 nodes influencing corneal myofibroblast development. The expression of a novel MXRA5 in corneal stroma and its association with corneal fibrosis was verified by real-time quantitative reverse transcription PCR and immunofluorescence. RNA-seq and gene count files were submitted to the NCBI Gene Expression Omnibus (GSE260476).

Conclusions

This study identified several novel genes involved in myofibroblast development, offering potential targets for developing newer therapeutic strategies for corneal fibrosis.

Enhancing schizophrenia phenotype prediction from genotype data through knowledge-driven deep neural network models

This article explores deep learning model design, drawing inspiration from the omnigenic model and genetic heterogeneity concepts, to improve schizophrenia prediction using genotype data. It introduces an innovative three-step approach leveraging neural networks' capabilities to efficiently handle genetic interactions. A locally connected network initially routes input data from variants to their corresponding genes. The second step employs an Encoder-Decoder to capture relationships among identified genes. The final model integrates knowledge from the first two and incorporates a parallel component to consider the effects of additional genes. This expansion enhances prediction scores by considering a larger number of genes. Trained models achieved an average AUC of 0.83, surpassing other genotype-trained models and matching gene expression dataset-based approaches. Additionally, tests on held-out sets reported an average sensitivity of 0.72 and an accuracy of 0.76, aligning with schizophrenia heritability predictions. Moreover, the study addresses genetic heterogeneity challenges by considering diverse population subsets.

Global profiling of functional histidines in live cells using small-molecule photosensitizer and chemical probe relay labelling

Recent advances in chemical proteomics have focused on developing chemical probes that react with nucleophilic amino acid residues. Although histidine is an attractive candidate due to its importance in enzymatic catalysis, metal binding and protein-protein interaction, its moderate nucleophilicity poses challenges. Its modification is frequently influenced by cysteine and lysine, which results in poor selectivity and narrow proteome coverage. Here we report a singlet oxygen and chemical probe relay labelling method that achieves high selectivity towards histidine. Libraries of small-molecule photosensitizers and chemical probes were screened to optimize histidine labelling, enabling histidine profiling in live cells with around 7,200 unique sites. Using NMR spectroscopy and X-ray crystallography, we characterized the reaction mechanism and the structures of the resulting products. We then applied this method to discover unannotated histidine sites key to enzymatic activity and metal binding in select metalloproteins. This method also revealed the accessibility change of histidine mediated by protein-protein interaction that influences select protein subcellular localization, underscoring its capability in discovering functional histidines.

Genomically recoded Escherichia coli with optimized functional phenotypes

Genomically recoded organisms hold promise for many biotechnological applications, but they may exhibit substantial fitness defects relative to their non-recoded counterparts. We used targeted metabolic screens, genetic analysis, and proteomics to identify the origins of fitness impairment in a model recoded organism, Escherichia coli C321.∆A. We found that defects in isoleucine biosynthesis and release factor activity, caused by mutations extant in all K-12 lineage strains, elicited profound fitness impairments in C321.∆A, suggesting that genome recoding exacerbates suboptimal traits present in precursor strains. By correcting these and other C321.∆A-specific mutations, we engineered C321.∆A strains with doubling time reductions of 17% and 42% in rich and minimal medium, respectively, compared to ancestral C321. Strains with improved growth kinetics also demonstrated enhanced ribosomal non-standard amino acid incorporation capabilities. Proteomic analysis indicated that C321.∆A lacks the ability to regulate essential amino acid and nucleotide biosynthesis pathways, and that targeted mutation reversion restored regulatory capabilities. Our work outlines a strategy for the rapid and precise phenotypic optimization of genomically recoded organisms and other engineered microbes.

BEAM: A combinatorial recombinase toolbox for binary gene expression and mosaic genetic analysis

We describe a binary expression aleatory mosaic (BEAM) system, which relies on DNA delivery by transfection or viral transduction along with nested recombinase activity to generate two genetically distinct, non-overlapping populations of cells for comparative analysis. Control cells labeled with red fluorescent protein (RFP) can be directly compared with experimental cells manipulated by genetic gain or loss of function and labeled with GFP. Importantly, BEAM incorporates recombinase-dependent signal amplification and delayed reporter expression to enable sharper delineation of control and experimental cells and to improve reliability relative to existing methods. We applied BEAM to a variety of known phenotypes to illustrate its advantages for identifying temporally or spatially aberrant phenotypes, for revealing changes in cell proliferation or death, and for controlling for procedural variability. In addition, we used BEAM to test the cortical protomap hypothesis at the individual radial unit level, revealing that area identity is cell autonomously specified in adjacent radial units.

Transcriptomic Meta-Analysis Identifies Upregulated Clotting and Fibrinolysis Pathways in Colorectal Cancer Tumors Containing Hereditary PMS2 Mismatch Repair Deficiency

Lynch Syndrome is characterized by deficient mismatch repair (dMMR) components. We performed a meta-analysis of multiple RNA-sequencing datasets from patients with different dMMR variants (PMS2, MLH1, and MSH2) to better characterize the unique transcriptional profiles. Our results reveal enriched signaling pathways from tumor samples with germline mutations in the PMS2 gene including upregulation in pathways related to intrinsic and extrinsic prothrombin activation, fibrinolysis, and uPA/uPAR-mediated signaling. These pathways have been associated with tumor growth, invasiveness, and metastasis. This work provides support for further exploration into the role of PMS2 in tumor development, and as a potential therapeutic mechanism.

Comprehensive proteomic analysis of HCoV-OC43 virions and virus-modulated extracellular vesicles

Viruses are obligate parasites that depend on the cellular machinery for their propagation. Several viruses also incorporate cellular proteins that facilitate viral spread. Defining these cellular proteins is critical to decipher viral life cycles and delineate novel therapeutic strategies. While numerous studies have explored the importance of host proteins in coronavirus spread, information about their presence in mature virions is limited. In this study, we developed a protocol to highly enrich mature HCoV-OC43 virions and characterize them by proteomics. Recognizing that cells release extracellular vesicles whose content is modulated by viruses, and given our ability to separate virions from these vesicles, we also analyzed their protein content in both uninfected and infected cells. We uncovered 69 unique cellular proteins associated with virions including 31 high-confidence hits. These proteins primarily regulate RNA metabolism, enzymatic activities, vesicular transport, cell adhesion, metabolite interconversion, and translation. We further discovered that the virus had a profound impact on exosome composition, incorporating 47 novel cellular proteins (11 high confidence) and excluding 92 others (61 high confidence) in virus-associated extracellular vesicles compared to uninfected cells. Moreover, a dsiRNA screen revealed that 11 of 18 select targets significantly impacted viral yields, including proteins found in virions or extracellular vesicles. Overall, this study provides new and important insights into the incorporation of numerous host proteins into HCoV-OC43 virions, their biological significance, and the ability of the virus to modulate extracellular vesicles.

IMPORTANCE

In recent years, coronaviruses have dominated global attention, making it crucial to develop methods to control them and prevent future pandemics. Besides viral proteins, host proteins play a significant role in viral propagation and offer potential therapeutic targets. Targeting host proteins is advantageous because they are less likely to mutate and develop resistance compared to viral proteins, a common issue with many antiviral treatments. In this study, we examined the protein content of the less virulent biosafety level 2 HCoV-OC43 virus as a stand-in for the more virulent SARS-CoV-2. Our findings reveal that several cellular proteins incorporated into the virion regulate viral spread. In addition, we report that the virus extensively modulates the content of extracellular vesicles, enhancing viral dissemination. This underscores the critical interplay between the virus, host proteins, and extracellular vesicles.

Deep learning methods for protein function prediction

Predicting protein function from protein sequence, structure, interaction, and other relevant information is important for generating hypotheses for biological experiments and studying biological systems, and therefore has been a major challenge in protein bioinformatics. Numerous computational methods had been developed to advance protein function prediction gradually in the last two decades. Particularly, in the recent years, leveraging the revolutionary advances in artificial intelligence (AI), more and more deep learning methods have been developed to improve protein function prediction at a faster pace. Here, we provide an in-depth review of the recent developments of deep learning methods for protein function prediction. We summarize the significant advances in the field, identify several remaining major challenges to be tackled, and suggest some potential directions to explore. The data sources and evaluation metrics widely used in protein function prediction are also discussed to assist the machine learning, AI, and bioinformatics communities to develop more cutting-edge methods to advance protein function prediction.

Characterisation of the tracheal transcriptional response of chickens to chronic infection with Mycoplasma synoviae

Mycoplasma synoviae causes infectious synovitis and respiratory tract infections in chickens and is responsible for significant economic losses in the poultry industry. Effective attachment and colonisation of the trachea is critical for the persistence of the organism and progression of the disease it causes. The respiratory tract infection is usually sub-clinical, but concurrent infection with infectious bronchitis virus (IBV) is known to enhance the pathogenicity of M. synoviae. This study aimed to explore differentially expressed genes in the tracheal mucosa, and their functional categories, during chronic infection with M. synoviae, using a M. synoviae-IBV infection model. The transcriptional profiles of the trachea were assessed 2 weeks after infection using RNA sequencing. In chickens infected with M. synoviae or IBV, only 1 or 8 genes were differentially expressed compared to uninfected chickens, respectively. In contrast, the M. synoviae-IBV infected chickens had 621 upregulated and 206 downregulated genes compared to uninfected chickens. Upregulated genes and their functional categories were suggestive of uncontrolled lymphoid cell proliferation and an ongoing pro-inflammatory response. Genes associated with anti-inflammatory effects, pathogen removal, apoptosis, regulation of the immune response, airway homoeostasis, cell adhesion and tissue regeneration were downregulated. Overall, transcriptional changes in the trachea, 2 weeks after infection with M. synoviae and IBV, indicate immune dysregulation, robust inflammation and a lack of cytotoxic damage during chronic infection. This model provides insights into the pathogenesis of chronic infection with M. synoviae.

Comparative Proteomic Analysis of Huh7 Cells Transfected with Sub-Saharan African Hepatitis B Virus (Sub)genotypes Reveals Potential Oncogenic Factors

In sub-Saharan Africa (SSA), the (sub)genotypes A1, D3, and E of the hepatitis B virus (HBV) prevail. Individuals infected with subgenotype A1 have a 4.5-fold increased risk of HCC compared to those infected with other (sub)genotypes. The effect of (sub)genotypes on protein expression and host signalling has not been studied. Mass spectrometry was used to analyse the proteome of Huh7 cells transfected with replication-competent clones. Proteomic analysis revealed significantly differentially expressed proteins between SSA (sub)genotypes. Different (sub)genotypes have the propensity to dysregulate specific host signalling pathways. Subgenotype A1 resulted in dysregulation within the Ras pathway. Ras-associated protein, RhoC, was significantly upregulated in cells transfected with subgenotype A1 compared to those transfected with other (sub)genotypes, on both a proteomic (>1.5-fold) and mRNA level (p < 0.05). Two of the main cellular signalling pathways involving RHOC, MAPK and PI3K/Akt/mTOR, regulate cell growth, motility, and survival. Downstream signalling products of these pathways have been shown to increase MMP2 and MMP9 expression. An extracellular MMP2 and MMP9 ELISA revealed a non-significant increase in MMP2 and MMP9 in the cells transfected with A1 compared to the other (sub)genotypes (p < 0.05). The upregulated Ras-associated proteins have been implicated as oncoproteins in various cancers and could contribute to the increased hepatocarcinogenic potential of A1.

Prediction of the most deleterious non-synonymous SNPs in the human IL1B gene: evidence from bioinformatics analyses

BACKGROUND

Polymorphisms in IL1B play a significant role in depression, multiple inflammatory-associated disorders, and susceptibility to infection. Functional non-synonymous SNPs (nsSNPs) result in changes in the encoded amino acids, potentially leading to structural and functional alterations in the mutant proteins. So far, most genetic studies have concentrated on SNPs located in the IL1B promoter region, without addressing nsSNPs and their association with multifactorial diseases. Therefore, this study aimed to explore the impact of deleterious nsSNPs retrieved from the dbSNP database on the structure and functions of the IL1B protein.

RESULTS

Six web servers (SIFT, PolyPhen-2, PROVEAN, SNPs&GO, PHD-SNP, PANTHER) were used to analyze the impact of 222 missense SNPs on the function and structure of IL1B protein. Five novel nsSNPs (E100K, T240I, S53Y, D128Y, and F228S) were found to be deleterious and had a mutational impact on the structure and function of the IL1B protein. The I-mutant v2.0 and MUPro servers predicted that these mutations decreased the stability of the IL1B protein. Additionally, these five mutations were found to be conserved, underscoring their significance in protein structure and function. Three of them (T240I, D128Y, and F228S) were predicted to be cancer-causing nsSNPs. To analyze the behavior of the mutant structures under physiological conditions, we conducted a 50 ns molecular dynamics simulation using the WebGro online tool. Our findings indicate that the mutant values differ from those of the IL1B wild type in terms of RMSD, RMSF, Rg, SASA, and the number of hydrogen bonds.

CONCLUSIONS

This study provides valuable insights into nsSNPs located in the coding regions of IL1B, which lead to direct deleterious effects on the functional and structural aspects of the IL1B protein. Thus, these nsSNPs could be considered significant candidates in the pathogenesis of disorders caused by IL1B dysfunction, contributing to effective drug discovery and the development of precision medications. Thorough research and wet lab experiments are required to verify our findings. Moreover, bioinformatic tools were found valuable in the prediction of deleterious nsSNPs.

Integrated Proteomics Analysis of Baseline Protein Expression in Pig Tissues

The availability of an increasingly large amount of public proteomics data sets presents an opportunity for performing combined analyses to generate comprehensive organism-wide protein expression maps across different organisms and biological conditions. Sus scrofa, a domestic pig, is a model organism relevant for food production and for human biomedical research. Here, we reanalyzed 14 public proteomics data sets from the PRIDE database coming from pig tissues to assess baseline (without any biological perturbation) protein abundance in 14 organs, encompassing a total of 20 healthy tissues from 128 samples. The analysis involved the quantification of protein abundance in 599 mass spectrometry runs. We compared protein expression patterns among different pig organs and examined the distribution of proteins across these organs. Then, we studied how protein abundances were compared across different data sets and studied the tissue specificity of the detected proteins. Of particular interest, we conducted a comparative analysis of protein expression between pig and human tissues, revealing a high degree of correlation in protein expression among orthologs, particularly in brain, kidney, heart, and liver samples. We have integrated the protein expression results into the Expression Atlas resource for easy access and visualization of the protein expression data individually or alongside gene expression data.

Network pharmacology, molecular docking, and molecular dynamics simulation to elucidate the mechanism of anti-aging action of Tinospora cordifolia

Scientific research has demonstrated that Tinospora cordifolia acts as an anti-aging agent in several experimental models, generating global interest in its underlying molecular mechanisms of this activity. The aim of the study was to identify the possible phytochemical compounds of T. cordifolia that might combat age-related illness through integrating network pharmacology, molecular docking techniques, and molecular dynamics (MD) study to explore their potential mechanisms of action. To carry out this study, several databases were used, including PubChem, KNApSAcK family database, PubMed, SwissADME, Molsoft, SwissTargetPrediction, GeneCards, and OMIM database. For network development and GO enrichment analysis KEGG, ShinyGo 0.77, and the STRING database were used. For better analysis, the networks were also constructed using Cytoscape 3.9.1. The Cytoscape network analyzer tool was used for data analysis, and molecular docking was done via Vina-GPU-2.0. The best compounds and AKT1 were finally subjected to MD simulation for 100 ns. The CytoHubba plugin of Cytoscape identified ten key targets, commonly called hub genes, including AKT1, GAPDH, and TP53, and so on. GO and KEGG pathway enrichment analysis revealed the relevant biological processes, cellular components, and molecular functions involved in treating aging-related disorders. KEGG pathway analysis involved neuroactive ligand-receptor interactions, lipid and atherosclerosis, and cAMP signaling. The docking of 100 T. cordifolia compounds with AKT1 demonstrated good binding affinity, particularly for Amritoside, Sitagliptin, Berberine, and Piperine. Finally, the relative stability of four-hit phytochemicals was validated by MD simulation, which may be the most crucial compound for anti-aging activity. In conclusion, this study used network pharmacology, molecular docking, and MD simulation to identify the compounds in T. cordifolia and proposed a potential mechanism for anti-aging activity. These results suggest future directions for the prevention and treatment of age-related diseases.

Cytidine deaminases APOBEC3C and APOBEC3D promote DNA replication stress resistance in pancreatic cancer cells

Gemcitabine is a potent inhibitor of DNA replication and is a mainstay therapeutic for diverse cancers, particularly pancreatic ductal adenocarcinoma (PDAC). However, most tumors remain refractory to gemcitabine therapies. Here, to define the cancer cell response to gemcitabine, we performed genome-scale CRISPR-Cas9 chemical-genetic screens in PDAC cells and found selective loss of cell fitness upon disruption of the cytidine deaminases APOBEC3C and APOBEC3D. Following gemcitabine treatment, APOBEC3C and APOBEC3D promote DNA replication stress resistance and cell survival by deaminating cytidines in the nuclear genome to ensure DNA replication fork restart and repair in PDAC cells. We provide evidence that the chemical-genetic interaction between APOBEC3C or APOBEC3D and gemcitabine is absent in nontransformed cells but is recapitulated across different PDAC cell lines, in PDAC organoids and in PDAC xenografts. Thus, we uncover roles for APOBEC3C and APOBEC3D in DNA replication stress resistance and offer plausible targets for improving gemcitabine-based therapies for PDAC.

Detecting outliers in case-control cohorts for improving deep learning networks on Schizophrenia prediction

This study delves into the intricate genetic and clinical aspects of Schizophrenia, a complex mental disorder with uncertain etiology. Deep Learning (DL) holds promise for analyzing large genomic datasets to uncover new risk factors. However, based on reports of non-negligible misdiagnosis rates for SCZ, case-control cohorts may contain outlying genetic profiles, hindering compelling performances of classification models. The research employed a case-control dataset sourced from the Swedish populace. A gene-annotation-based DL architecture was developed and employed in two stages. First, the model was trained on the entire dataset to highlight differences between cases and controls. Then, samples likely to be misclassified were excluded, and the model was retrained on the refined dataset for performance evaluation. The results indicate that SCZ prevalence and misdiagnosis rates can affect case-control cohorts, potentially compromising future studies reliant on such datasets. However, by detecting and filtering outliers, the study demonstrates the feasibility of adapting DL methodologies to large-scale biological problems, producing results more aligned with existing heritability estimates for SCZ. This approach not only advances the comprehension of the genetic background of SCZ but also opens doors for adapting DL techniques in complex research for precision medicine in mental health.

Multiomics Analysis of the PHLDA Gene Family in Different Cancers and Their Clinical Prognostic Value

The PHLDA (pleckstrin homology-like domain family) gene family is popularly known as a potential biomarker for cancer identification, and members of the PHLDA family have become considered potentially viable targets for cancer treatments. The PHLDA gene family consists of PHLDA1, PHLDA2, and PHLDA3. The predictive significance of PHLDA genes in cancer remains unclear. To determine the role of pleckstrin as a prognostic biomarker in human cancers, we conducted a systematic multiomics investigation. Through various survival analyses, pleckstrin expression was evaluated, and their predictive significance in human tumors was discovered using a variety of online platforms. By analyzing the protein-protein interactions, we also chose a collection of well-known functional protein partners for pleckstrin. Investigations were also carried out on the relationship between pleckstrins and other cancers regarding mutations and copy number alterations. The cumulative impact of pleckstrin and their associated genes on various cancers, Gene Ontology (GO), and pathway analyses were used for their evaluation. Thus, the expression profiles of PHLDA family members and their prognosis in various cancers may be revealed by this study. During this multiomics analysis, we found that among the PHLDA family, PHLDA1 may be a therapeutic target for several cancers, including kidney, colon, and brain cancer, while PHLDA2 can be a therapeutic target for cancers of the colon, esophagus, and pancreas. Additionally, PHLDA3 may be a useful therapeutic target for ovarian, renal, and gastric cancer.

Physiochemical interaction between osmotic stress and a bacterial exometabolite promotes plant disease

Various microbes isolated from healthy plants are detrimental under laboratory conditions, indicating the existence of molecular mechanisms preventing disease in nature. Here, we demonstrated that application of sodium chloride (NaCl) in natural and gnotobiotic soil systems is sufficient to induce plant disease caused by an otherwise non-pathogenic root-derived Pseudomonas brassicacearum isolate (R401). Disease caused by combinatorial treatment of NaCl and R401 triggered extensive, root-specific transcriptional reprogramming that did not involve down-regulation of host innate immune genes, nor dampening of ROS-mediated immunity. Instead, we identified and structurally characterized the R401 lipopeptide brassicapeptin A as necessary and sufficient to promote disease on salt-treated plants. Brassicapeptin A production is salt-inducible, promotes root colonization and transitions R401 from being beneficial to being detrimental on salt-treated plants by disturbing host ion homeostasis, thereby bolstering susceptibility to osmolytes. We conclude that the interaction between a global change stressor and a single exometabolite from a member of the root microbiome promotes plant disease in complex soil systems.

Oct4 redox sensitivity potentiates reprogramming and differentiation

The transcription factor Oct4/Pou5f1 is a component of the regulatory circuitry governing pluripotency and is widely used to induce pluripotency from somatic cells. Here we used domain swapping and mutagenesis to study Oct4's reprogramming ability, identifying a redox-sensitive DNA binding domain, cysteine residue (Cys48), as a key determinant of reprogramming and differentiation. Oct4 Cys48 sensitizes the protein to oxidative inhibition of DNA binding activity and promotes oxidation-mediated protein ubiquitylation. Pou5f1 C48S point mutation has little effect on undifferentiated embryonic stem cells (ESCs) but upon retinoic acid (RA) treatment causes retention of Oct4 expression, deregulated gene expression, and aberrant differentiation. Pou5f1 C48S ESCs also form less differentiated teratomas and contribute poorly to adult somatic tissues. Finally, we describe Pou5f1 C48S (Janky) mice, which in the homozygous condition are severely developmentally restricted after E4.5. Rare animals bypassing this restriction appear normal at birth but are sterile. Collectively, these findings uncover a novel Oct4 redox mechanism involved in both entry into and exit from pluripotency.

Identification of cancer risk groups through multi-omics integration using autoencoder and tensor analysis

Identifying cancer risk groups by multi-omics has attracted researchers in their quest to find biomarkers from diverse risk-related omics. Stratifying the patients into cancer risk groups using genomics is essential for clinicians for pre-prevention treatment to improve the survival time for patients and identify the appropriate therapy strategies. This study proposes a multi-omics framework that can extract the features from various omics simultaneously. The framework employs autoencoders to learn the non-linear representation of the data and applies tensor analysis for feature learning. Further, the clustering method is used to stratify the patients into multiple cancer risk groups. Several omics were included in the experiments, namely methylation, somatic copy-number variation (SCNV), micro RNA (miRNA) and RNA sequencing (RNAseq) from two cancer types, including Glioma and Breast Invasive Carcinoma from the TCGA dataset. The results of this study are promising, as evidenced by the survival analysis and classification models, which outperformed the state-of-the-art. The patients can be significantly (p-value<0.05) divided into risk groups using extracted latent variables from the fused multi-omics data. The pipeline is open source to help researchers and clinicians identify the patients' risk groups using genomics.

Activity-dependent FosB gene expression negatively regulates mast cell functions

Mast cells are innate immune cells that play a crucial role in numerous physiological processes across tissues by releasing pre-stored and newly synthesized mediators in response to stimuli, an activity largely driven by changes in gene expression. Given their widespread influence, dysfunction in mast cells can contribute to a variety of pathologies including allergies, long COVID, and autoimmune and neuroinflammatory disorders. Despite this, the specific transcriptional mechanisms that control mast cell mediator release remain poorly understood, significantly hindering the development of effective therapeutic strategies. We found that the two proteins encoded by the transcription factor FosB, FOSB and the highly stable variant ΔFOSB, are robustly expressed upon stimulation in both murine and human mast cell progenitors. Motivated by these findings, we generated a novel mouse model with targeted ablation of FosB gene expression specifically in mast cells (MC FosB- ) by crossing a mast cell-specific Cre reporter line (Mcpt5-Cre) with a Cre-dependent floxed FosB mouse lines. We found that mast cell progenitors derived from MC FosB- mice, compared to wild types (WT), exhibit baseline increased histamine content and vesicle numbers. Additionally, they show enhanced calcium mobilization, degranulation, and histamine release following allergy-related IgE-mediated stimulation, along with heightened IL-6 release in response to infection-like LPS stimulation. In vivo experiments with IgE- mediated and LPS challenges revealed that MC FosB- mice experience greater drops in body temperature, heightened activation of tissue-resident mast cells, and increased release of pro-inflammatory mediators compared to their WT counterparts. These findings suggest that FosB products play a crucial regulatory role in moderating stimulus-induced mast cell activation in response to both IgE and LPS stimuli. Lastly, by integrating CUT&RUN and RNAseq data, we identified several genes targeted by ΔFOSB that could mediate these observed effects, including Mir155hg, CLCF1, DUSP4, and Trib1. Together, this study provides the first evidence that FOSB/ΔFOSB modulate mast cell functions and provides a new possible target for therapeutic interventions aimed at ameliorating mast cell-related diseases.

Molecular Regulation of Fetal Brain Development in Inbred and Congenic Mouse Strains Differing in Longevity

The objective of this study was to investigate gene regulation of the developing fetal brain from congenic or inbred mice strains that differed in longevity. Gene expression and alternative splice variants were analyzed in a genome-wide manner in the fetal brain of C57BL/6J mice (long-lived) in comparison to B6.Cg-Cav1tm1Mls/J (congenic, short-lived) and AKR/J (inbred, short-lived) mice on day(d) 12, 15, and 17 of gestation. The analysis showed a contrasting gene expression pattern during fetal brain development in these mice. Genes related to brain development, aging, and the regulation of alternative splicing were significantly differentially regulated in the fetal brain of the short-lived compared to long-lived mice during development from d15 and d17. A significantly reduced number of splice variants was observed on d15 compared to d12 or d17 in a strain-dependent manner. An epigenetic clock analysis of d15 fetal brain identified DNA methylations that were significantly associated with single-nucleotide polymorphic sites between AKR/J and C57BL/6J strains. These methylations were associated with genes that show epigenetic changes in an age-correlated manner in mice. Together, the finding of this study suggest that fetal brain development and longevity are epigenetically linked, supporting the emerging concept of the early-life origin of longevity.

The association of protein-bound methionine sulfoxide with proteomic basis for aging in beech seeds

BACKGROUND

European beech (Fagus sylvatica L.) trees produce seeds irregularly; therefore, it is necessary to store beech seeds for forestation. Despite the acquisition of desiccation tolerance during development, beech seeds are classified as intermediate because they lose viability during long-term storage faster than typical orthodox seeds. In this study, beech seeds stored for short (3 years) or long (20 years) periods under optimal conditions and displaying 92 and 30% germination capacity, respectively, were compared.

RESULTS

Aged seeds displayed increased membrane damage, manifested as electrolyte leakage and lipid peroxidation levels. Analyses have been based on embryonic axes, which contained higher levels of reactive oxygen species (ROS) and higher levels of protein-bound methionine sulfoxide (MetO) in aged seeds. Using label-free quantitative proteomics, 3,949 proteins were identified, of which 2,442 were reliably quantified pointing to 24 more abundant proteins and 35 less abundant proteins in beech seeds under long-term storage conditions. Functional analyses based on gene ontology annotations revealed that nucleic acid binding activity (molecular function), ribosome organization or biogenesis and transmembrane transport (cellular processes), translational proteins (protein class) and membranous anatomical entities (cellular compartment) were affected in aged seeds. To verify whether MetO, the oxidative posttranslational modification of proteins that can be reversed via the action of methionine sulfoxide reductase (Msr) enzymes, is involved in the aging of beech seeds, we identified and quantified 226 MetO-containing proteins, among which 9 and 19 exhibited significantly up- and downregulated MetO levels, respectively, in beech seeds under long-term storage conditions. Several Msr isoforms were identified and recognized as MsrA1-like, MsrA4, MsrB5 and MsrB5-like in beech seeds. Only MsrA1-like displayed decreased abundance in aged seeds.

CONCLUSIONS

We demonstrated that the loss of membrane integrity reflected in the elevated abundance of membrane proteins had a higher impact on seed aging progress than the MetO/Msr system. Proteome analyses enabled us to propose protein Sec61 and glyceraldehyde-3-phosphate dehydrogenase as potential longevity modulators in beech seeds.

The Arabidopsis Information Resource in 2024

Since 1999, The Arabidopsis Information Resource (www.arabidopsis.org) has been curating data about the Arabidopsis thaliana genome. Its primary focus is integrating experimental gene function information from the peer-reviewed literature and codifying it as controlled vocabulary annotations. Our goal is to produce a "gold standard" functional annotation set that reflects the current state of knowledge about the Arabidopsis genome. At the same time, the resource serves as a nexus for community-based collaborations aimed at improving data quality, access, and reuse. For the past decade, our work has been made possible by subscriptions from our global user base. This update covers our ongoing biocuration work, some of our modernization efforts that contribute to the first major infrastructure overhaul since 2011, the introduction of JBrowse2, and the resource's role in community activities such as organizing the structural reannotation of the genome. For gene function assessment, we used gene ontology annotations as a metric to evaluate: (1) what is currently known about Arabidopsis gene function and (2) the set of "unknown" genes. Currently, 74% of the proteome has been annotated to at least one gene ontology term. Of those loci, half have experimental support for at least one of the following aspects: molecular function, biological process, or cellular component. Our work sheds light on the genes for which we have not yet identified any published experimental data and have no functional annotation. Drawing attention to these unknown genes highlights knowledge gaps and potential sources of novel discoveries.

Nfe2l3 promotes neuroprotection and long-distance axon regeneration after injury in vivo

Nuclear factor erythroid 2 like (Nfe2l) gene family members 1-3 mediate cellular response to oxidative stress, including in the central nervous system (CNS). However, neuronal functions of Nfe2l3 are unknown. Here, we comparatively evaluated expression of Nfe2l1, Nfe2l2, and Nfe2l3 in singe cell RNA-seq (scRNA-seq)-profiled cortical and retinal ganglion cell (RGC) CNS projection neurons, investigated whether Nfe2l3 regulates neuroprotection and axon regeneration after CNS injury in vivo, and characterized a gene network associated with Nfe2l3 in neurons. We showed that, Nfe2l3 expression transiently peaks in developing immature cortical and RGC projection neurons, but is nearly abolished in adult neurons and is not upregulated after injury. Furthermore, within the retina, Nfe2l3 is enriched in RGCs, primarily neonatally, and not upregulated in injured RGCs, whereas Nfe2l1 and Nfe2l2 are expressed robustly in other retinal cell types as well and are upregulated in injured RGCs. We also found that, expressing Nfe2l3 in injured RGCs through localized intralocular viral vector delivery promotes neuroprotection and long-distance axon regeneration after optic nerve injury in vivo. Moreover, Nfe2l3 provided a similar extent of neuroprotection and axon regeneration as viral vector-targeting of Pten and Klf9, which are prominent regulators of neuroprotection and long-distance axon regeneration. Finally, we bioinformatically characterized a gene network associated with Nfe2l3 in neurons, which predicted the association of Nfe2l3 with established mechanisms of neuroprotection and axon regeneration. Thus, Nfe2l3 is a novel neuroprotection and axon regeneration-promoting factor with a therapeutic potential for treating CNS injury and disease.

Using the Bayesian variational spike and slab model in a genome-wide association study for finding associated loci with bipolar disorder

OBJECTIVE

The genome-wide association studies (GWAS) analysis, the most successful technique for discovering disease-related genetic variation, has some statistical concerns, including multiple testing, the correlation among variants (single-nucleotide polymorphisms) based on linkage disequilibrium and omitting the important variants when fitting the model with just one variant. To eliminate these problems in a small sample-size study, we used a sparse Bayesian learning model for finding bipolar disorder (BD) genetic variants.

METHODS

This study used the Wellcome Trust Case Control Consortium data set, including 1998 BD cases and 1500 control samples, and after quality control, 380,628 variants were analysed. In this GWAS, a Bayesian logistic model with hierarchical shrinkage spike and slab priors was used, with all variants considered simultaneously in one model. In order to decrease the computational burden, an alternative inferential method, Bayesian variational inference, has been used.

RESULTS

Thirteen variants were selected as associated with BD. The three of them (rs7572953, rs1378850 and rs4148944) were reported in previous GWAS. Eight of which were related to hemogram parameters, such as lymphocyte percentage, plateletcrit and haemoglobin concentration. Among selected related genes, GABPA, ELF3 and JAM2 were enriched in the platelet-derived growth factor pathway. These three genes, along with APP, ARL8A, CDH23 and GPR37L1, could be differential diagnostic variants for BD.

CONCLUSIONS

By reducing the statistical restrictions of GWAS analysis, the application of the Bayesian variational spike and slab models can offer insight into the genetic link with BD even with a small sample size. To uncover related variations with other traits, this model needs to be further examined.

The effects of resistance training on denervated myofibers, senescent cells, and associated protein markers in middle-aged adults

Denervated myofibers and senescent cells are hallmarks of skeletal muscle aging. However, sparse research has examined how resistance training affects these outcomes. We investigated the effects of unilateral leg extensor resistance training (2 days/week for 8 weeks) on denervated myofibers, senescent cells, and associated protein markers in apparently healthy middle-aged participants (MA, 55 ± 8 years old, 17 females, 9 males). We obtained dual-leg vastus lateralis (VL) muscle cross-sectional area (mCSA), VL biopsies, and strength assessments before and after training. Fiber cross-sectional area (fCSA), satellite cells (Pax7+), denervated myofibers (NCAM+), senescent cells (p16+ or p21+), proteins associated with denervation and senescence, and senescence-associated secretory phenotype (SASP) proteins were analyzed from biopsy specimens. Leg extensor peak torque increased after training (p < .001), while VL mCSA trended upward (interaction p = .082). No significant changes were observed for Type I/II fCSAs, NCAM+ myofibers, or senescent (p16+ or p21+) cells, albeit satellite cells increased after training (p = .037). While >90% satellite cells were not p16+ or p21+, most p16+ and p21+ cells were Pax7+ (>90% on average). Training altered 13 out of 46 proteins related to muscle-nerve communication (all upregulated, p < .05) and 10 out of 19 proteins related to cellular senescence (9 upregulated, p < .05). Only 1 out of 17 SASP protein increased with training (IGFBP-3, p = .031). In conclusion, resistance training upregulates proteins associated with muscle-nerve communication in MA participants but does not alter NCAM+ myofibers. Moreover, while training increased senescence-related proteins, this coincided with an increase in satellite cells but not alterations in senescent cell content or SASP proteins. These latter findings suggest shorter term resistance training is an unlikely inducer of cellular senescence in apparently healthy middle-aged participants. However, similar study designs are needed in older and diseased populations before definitive conclusions can be drawn.

Network pharmacology-based approach to elucidate the pharmacologic mechanisms of natural compounds from Dictyostelium discoideum for Alzheimer's disease treatment

Alzheimer's disease (AD) is increasingly becoming a major public health concern in our society. While many studies have explored the use of natural polyketides, alkaloids, and other chemical components in AD treatment, there is an urgent need to clarify the concept of multi-target treatment for AD. This study focuses on using network pharmacology approach to elucidate how secondary metabolites from Dictyostelium discoideum affect AD through multi-target or indirect mechanisms. The secondary metabolites produced by D. discoideum during their development were obtained from literature sources and PubChem. Disease targets were selected using GeneCards, DisGeNET, and CTD databases, while compound-based targets were identified through Swiss target prediction and Venn diagrams were used to find intersections between these targets. A network depicting the interplay among disease, drugs, active ingredients, and key target proteins (PPI network) was formed utilizing the STRING (Protein-Protein Interaction Networks Functional Enrichment Analysis) database. To anticipate the function and mechanism of the screened compounds, GO and KEGG enrichment analyses were conducted and visually presented using graphs and bubble charts. After the screening phase, the top interacting targets in the PPI network and the compound with the most active target were chosen for subsequent molecular docking and molecular dynamic simulation studies. This study identified nearly 50 potential targeting genes for each of the screened compounds and revealed multiple signaling pathways. Among these pathways, the inflammatory pathway stood out. COX-2, a receptor associated with neuroinflammation, showed differential expression in various stages of AD, particularly in pyramidal neurons during the early stages of the disease. This increase in COX-2 expression is likely induce by higher levels of IL-1, which is associated with neuritic plaques and microglial cells in AD. Molecular docking investigations demonstrated a strong binding interaction between the terpene compound PQA-11 and the neuroinflammatory receptor COX2, with a substantial binding affinity of -8.4 kcal/mol. Subsequently, a thorough analysis of the docked complex (COX2-PQA11) through Molecular Dynamics Simulation showed lower RMSD, minimal RMSF fluctuations, and a reduced total energy of -291.35 kJ/mol compared to the standard drug. These findings suggest that the therapeutic effect of PQA-11 operates through the inflammatory pathway, laying the groundwork for further in-depth research into the role of secondary metabolites in AD treatment.

Comparative Single Cell Analysis of Transcriptional Bursting Reveals the Role of Genome Organization on de novo Transcript Origination

Spermatogenesis is a key developmental process underlying the origination of newly evolved genes. However, rapid cell type-specific transcriptomic divergence of the Drosophila germline has posed a significant technical barrier for comparative single-cell RNA-sequencing (scRNA-Seq) studies. By quantifying a surprisingly strong correlation between species-and cell type-specific divergence in three closely related Drosophila species, we apply a simple statistical procedure to identify a core set of 198 genes that are highly predictive of cell type identity while remaining robust to species-specific differences that span over 25-30 million years of evolution. We then utilize cell type classifications based on the 198-gene set to show how transcriptional divergence in cell type increases throughout spermatogenic developmental time, contrasting with traditional hourglass models of whole-organism development. With these cross-species cell type classifications, we then investigate the influence of genome organization on the molecular evolution of spermatogenesis vis-a-vis transcriptional bursting. We first demonstrate how mechanistic control of pre-meiotic transcription is achieved by altering transcriptional burst size while post-meiotic control is exerted via altered bursting frequency. We then report how global differences in autosomal vs. X chromosomal transcription likely arise in a developmental stage preceding full testis organogenesis by showing evolutionarily conserved decreases in X-linked transcription bursting kinetics in all examined somatic and germline cell types. Finally, we provide evidence supporting the cultivator model of de novo gene origination by demonstrating how the appearance of newly evolved testis-specific transcripts potentially provides short-range regulation of the transcriptional bursting properties of neighboring genes during key stages of spermatogenesis.

Discovery and Verification of Sjögren's Syndrome Protein Biomarkers in Tears by Targeted LC-MRM

Sjögren's syndrome (SS) is an autoimmune rheumatic disorder characterized by exocrine gland dysfunction, mainly from the lacrimal and salivary glands. The disease causes severe aqueous dry eye syndrome (DED) and is associated with high rates of complications, including corneal ulceration, scaring, and perforation. Systemic complications may occur as well as a higher risk of developing lymphoma. Diagnosis of SS-DED is often delayed and difficult to establish. With the aim of discovering biomarkers to help discriminate SS-DED patients, a combination of untargeted and targeted LC-MS/MS analyses were performed on tear samples collected on Schirmer strips and subjected to tryptic digestion. Following the analysis of three cohorts and the development of two targeted LC-sMRM methods for the verification of putative biomarkers found in the first cohort of samples, 64 proteins could be linked to Sjögren's syndrome, in the hopes of helping to confirm diagnoses as well as potentially stratifying the severity of disease in these patients. Proteins that were increased in SS-DED showed activation of the immune system and alterations in homeostasis. Several proteases and protease inhibitors were found to be significantly changing in SS-DED, as well as a consistent decrease in specific proteins known to be secreted by the lacrimal gland.

Genome-wide association studies reveal differences in genetic susceptibility between single events vs. recurrent events of atrial fibrillation and myocardial infarction: the HUNT study

Genetic research into atrial fibrillation (AF) and myocardial infarction (MI) has predominantly focused on comparing afflicted individuals with their healthy counterparts. However, this approach lacks granularity, thus overlooking subtleties within patient populations. In this study, we explore the distinction between AF and MI patients who experience only a single disease event and those experiencing recurrent events. Integrating hospital records, questionnaire data, clinical measurements, and genetic data from more than 500,000 HUNT and United Kingdom Biobank participants, we compare both clinical and genetic characteristics between the two groups using genome-wide association studies (GWAS) meta-analyses, phenome-wide association studies (PheWAS) analyses, and gene co-expression networks. We found that the two groups of patients differ in both clinical characteristics and genetic risks. More specifically, recurrent AF patients are significantly younger and have better baseline health, in terms of reduced cholesterol and blood pressure, than single AF patients. Also, the results of the GWAS meta-analysis indicate that recurrent AF patients seem to be at greater genetic risk for recurrent events. The PheWAS and gene co-expression network analyses highlight differences in the functions associated with the sets of single nucleotide polymorphisms (SNPs) and genes for the two groups. However, for MI patients, we found that those experiencing single events are significantly younger and have better baseline health than those with recurrent MI, yet they exhibit higher genetic risk. The GWAS meta-analysis mostly identifies genetic regions uniquely associated with single MI, and the PheWAS analysis and gene co-expression networks support the genetic differences between the single MI and recurrent MI groups. In conclusion, this work has identified novel genetic regions uniquely associated with single MI and related PheWAS analyses, as well as gene co-expression networks that support the genetic differences between the patient subgroups of single and recurrent occurrence for both MI and AF.

Group 3 medulloblastoma transcriptional networks collapse under domain specific EP300/CBP inhibition

Chemical discovery efforts commonly target individual protein domains. Many proteins, including the EP300/CBP histone acetyltransferases (HATs), contain several targetable domains. EP300/CBP are critical gene-regulatory targets in cancer, with existing high potency inhibitors of either the catalytic HAT domain or protein-binding bromodomain (BRD). A domain-specific inhibitory approach to multidomain-containing proteins may identify exceptional-responding tumor types, thereby expanding a therapeutic index. Here, we discover that targeting EP300/CBP using the domain-specific inhibitors, A485 (HAT) or CCS1477 (BRD) have different effects in select tumor types. Group 3 medulloblastoma (G3MB) cells are especially sensitive to BRD, compared with HAT inhibition. Structurally, these effects are mediated by the difluorophenyl group in the catalytic core of CCS1477. Mechanistically, bromodomain inhibition causes rapid disruption of genetic dependency networks that are required for G3MB growth. These studies provide a domain-specific structural foundation for drug discovery efforts targeting EP300/CBP and identify a selective role for the EP300/CBP bromodomain in maintaining genetic dependency networks in G3MB.

MicroRNAs from edible plants reach the human gastrointestinal tract and may act as potential regulators of gene expression

MicroRNAs (miRNAs) are small single-stranded non-coding RNA molecules that regulate gene expression at the post-transcriptional level. A cross-kingdom regulatory function has been unveiled for plant miRNAs (xenomiRs), which could shape inter-species interactions of plants with other organisms (bacteria and humans) and thus, be key functional molecules of plant-based food in mammals. However, discrepancies regarding the stability and bioavailability of dietary plant miRNAs on the host cast in doubt whether these molecules could have a significant impact on human physiology. The aim of the present study was to identify miRNAs in edible plants and determine their bioavailability on humans after an acute intake of plant-based products. It was found that plant food, including fruits, vegetables and greens, nuts, legumes, and cereals, contains a wide range of miRNAs. XenomiRs miR156e, miR159 and miR162 were detected in great abundance in edible plants and were present among many plant foods, and thus, they were selected as candidates to analyse their bioavailability in humans. These plant miRNAs resisted cooking processes (heat-treatments) and their relative presence increased in faeces after and acute intake of plant-based foods, although they were not detected in serum. Bioinformatic analysis revealed that these miRNAs could potentially target human and bacterial genes involved in processes such as cell signalling and metabolism. In conclusion, edible plants contain miRNAs, such as miR156e, miR159 and miR162, that could resist degradation during cooking and digestion and reach the distal segments of the gastrointestinal tract. Nevertheless, strategies should be developed to improve their absorption to potentially reach host tissues and organs and modulate human physiology.

Balancing selection and the functional effects of shared polymorphism in cryptic Daphnia species

The patterns of genetic variation within and between related taxa represent the genetic history of a species. Shared polymorphisms, loci with identical alleles across species, are of unique interest as they may represent cases of ancient selection maintaining functional variation post-speciation. In this study, we investigate the abundance of shared polymorphism in the Daphnia pulex species complex. We test whether shared mutations are consistent with the action of balancing selection or alternative hypotheses such as hybridization, incomplete lineage sorting, or convergent evolution. We analyzed over 2,000 genomes from North American and European D. pulex and several outgroup species to examine the prevalence and distribution of shared alleles between the focal species pair, North American and European D. pulex. We show that while North American and European D. pulex diverged over ten million years ago, they retained tens of thousands of shared alleles. We found that the number of shared polymorphisms between North American and European D. pulex cannot be explained by hybridization or incomplete lineage sorting alone. Instead, we show that most shared polymorphisms could be the product of convergent evolution, that a limited number appear to be old trans-specific polymorphisms, and that balancing selection is affecting young and ancient mutations alike. Finally, we provide evidence that a blue wavelength opsin gene with trans-specific polymorphisms has functional effects on behavior and fitness in the wild. Ultimately, our findings provide insights into the genetic basis of adaptation and the maintenance of genetic diversity between species.

Truncated protein isoforms generate diversity of protein localization and function in yeast

Genome-wide measurement of ribosome occupancy on mRNAs has enabled empirical identification of translated regions, but high-confidence detection of coding regions that overlap annotated coding regions has remained challenging. Here, we report a sensitive and robust algorithm that revealed the translation of 388 N-terminally truncated proteins in budding yeast-more than 30-fold more than previously known. We extensively experimentally validated them and defined two classes. The first class lacks large portions of the annotated protein and tends to be produced from a truncated transcript. We show that two such cases, Yap5truncation and Pus1truncation, have condition-specific regulation and distinct functions from their respective annotated isoforms. The second class of truncated protein isoforms lacks only a small region of the annotated protein and is less likely to be produced from an alternative transcript isoform. Many display different subcellular localizations than their annotated counterpart, representing a common strategy for dual localization of otherwise functionally identical proteins. A record of this paper's transparent peer review process is included in the supplemental information.

Disruption of Cholinergic Retinal Waves Alters Visual Cortex Development and Function

Retinal waves represent an early form of patterned spontaneous neural activity in the visual system. These waves originate in the retina before eye-opening and propagate throughout the visual system, influencing the assembly and maturation of subcortical visual brain regions. However, because it is technically challenging to ablate retina-derived cortical waves without inducing compensatory activity, the role these waves play in the development of the visual cortex remains unclear. To address this question, we used targeted conditional genetics to disrupt cholinergic retinal waves and their propagation to select regions of primary visual cortex, which largely prevented compensatory patterned activity. We find that loss of cholinergic retinal waves without compensation impaired the molecular and synaptic maturation of excitatory neurons located in the input layers of visual cortex, as well as layer 1 interneurons. These perinatal molecular and synaptic deficits also relate to functional changes observed at later ages. We find that the loss of perinatal cholinergic retinal waves causes abnormal visual cortex retinotopy, mirroring changes in the retinotopic organization of gene expression, and additionally impairs the processing of visual information. We further show that retinal waves are necessary for higher order processing of sensory information by impacting the state-dependent activity of layer 1 interneurons, a neuronal type that shapes neocortical state-modulation, as well as for state-dependent gain modulation of visual responses of excitatory neurons. Together, these results demonstrate that a brief targeted perinatal disruption of patterned spontaneous activity alters early cortical gene expression as well as synaptic and physiological development, and compromises both fundamental and, notably, higher-order functions of visual cortex after eye-opening.

In Silico and In Vitro Study of Isoquercitrin against Kidney Cancer and Inflammation by Triggering Potential Gene Targets

Kidney cancer has emerged as a major medical problem in recent times. Multiple compounds are used to treat kidney cancer by triggering cancer-causing gene targets. For instance, isoquercitrin (quercetin-3-O-β-d-glucopyranoside) is frequently present in fruits, vegetables, medicinal herbs, and foods and drinks made from plants. Our previous study predicted using protein-protein interaction (PPI) and molecular docking analysis that the isoquercitrin compound can control kidney cancer and inflammation by triggering potential gene targets of IGF1R, PIK3CA, IL6, and PTGS2. So, the present study is about further in silico and in vitro validation. We performed molecular dynamic (MD) simulation, gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, cytotoxicity assay, and RT-PCR and qRT-PCR validation. According to the MD simulation (250 ns), we found that IGF1R, PIK3CA, and PTGS2, except for IL6 gene targets, show stable binding energy with a stable complex with isoquercitrin. We also performed gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses of the final targets to determine their regulatory functions and signaling pathways. Furthermore, we checked the cytotoxicity effect of isoquercitrin (IQ) and found that 5 μg/mL and 10 μg/mL doses showed higher cell viability in a normal kidney cell line (HEK 293) and also inversely showed an inhibition of cell growth at 35% and 45%, respectively, in the kidney cancer cell line (A498). Lastly, the RT-PCR and qRT-PCR findings showed a significant decrease in PTGS2, PIK3CA, and IGF1R gene expression, except for IL6 expression, following dose-dependent treatments with IQ. Thus, we can conclude that isoquercitrin inhibits the expression of PTGS2, PIK3CA, and IGF1R gene targets, which in turn controls kidney cancer and inflammation.

Hopanoid lipids promote soybean-Bradyrhizobium symbiosis

The symbioses between leguminous plants and nitrogen-fixing bacteria known as rhizobia are well known for promoting plant growth and sustainably increasing soil nitrogen. Recent evidence indicates that hopanoids, a family of steroid-like lipids, promote Bradyrhizobium symbioses with tropical legumes. To characterize hopanoids in Bradyrhizobium symbiosis with soybean, we validated a recently published cumate-inducible hopanoid mutant of Bradyrhizobium diazoefficiens USDA110, Pcu-shc::∆shc. GC-MS analysis showed that this strain does not produce hopanoids without cumate induction, and under this condition, is impaired in growth in rich medium and under osmotic, temperature, and pH stress. In planta, Pcu-shc::∆shc is an inefficient soybean symbiont with significantly lower rates of nitrogen fixation and low survival within the host tissue. RNA-seq revealed that hopanoid loss reduces the expression of flagellar motility and chemotaxis-related genes, further confirmed by swim plate assays, and enhances the expression of genes related to nitrogen metabolism and protein secretion. These results suggest that hopanoids provide a significant fitness advantage to B. diazoefficiens in legume hosts and provide a foundation for future mechanistic studies of hopanoid function in protein secretion and motility.

A major problem for global sustainability is feeding our exponentially growing human population while available arable land decreases. Harnessing the power of plant-beneficial microbes is a potential solution, including increasing our reliance on the symbioses of leguminous plants and nitrogen-fixing rhizobia. This study examines the role of hopanoid lipids in the symbiosis between Bradyrhizobium diazoefficiens USDA110, an important commercial inoculant strain, and its economically significant host soybean. Our research extends our knowledge of the functions of bacterial lipids in symbiosis to an agricultural context, which may one day help improve the practical applications of plant-beneficial microbes in agriculture.