Nat Genet. 2025 Jun 12. doi: 10.1038/s41588-025-02218-x. Online ahead of print.

ABSTRACT

Studying the pathogenesis of human-adapted microorganisms is challenging, since small animal models often fail to recapitulate human physiology. Hence, the comprehensive genetic and regulatory circuits driving the infection process of principal human pathogens such as Shigella flexneri remain to be defined. We combined large-scale Shigella infections of enteroids and colonoids with transposon-directed insertion sequencing and Bayesian statistical modeling to address infection bottlenecks, thereby establishing the comprehensive genome-wide map of Shigella genes required to infect human intestinal epithelium. This revealed the Shigella virulence effectors essential for epithelial cell colonization across geometries and intestinal segments, identified over 100 chromosomal genes involved in the process and uncovered a post-transcriptional mechanism whereby tRNA-modification enzymes and differential codon usage exert global control of a bacterial virulence program. Our findings provide a broadly applicable framework for combining advanced organotypic tissue culture with functional genomics and computational tools to map human-microorganism interactions at scale.

PMID:40506541 | DOI:10.1038/s41588-025-02218-x

Nat Genet. 2025 Jun 12. doi: 10.1038/s41588-025-02220-3. Online ahead of print.

ABSTRACT

Methods that analyze single-cell paired RNA sequencing (RNA-seq) and assay for transposase-accessible chromatin using sequencing (ATAC-seq) multiome data have shown promise in linking regulatory elements to genes. However, existing methods exhibit low concordance and do not capture the effects of genomic distance. We propose pgBoost, an integrative modeling framework that trains a non-linear combination of existing linking strategies (including genomic distance) on expression quantitative trait locus (eQTL) data to assign a probabilistic score to each candidate single-nucleotide polymorphism-gene link. pgBoost attained higher enrichment than existing methods for evaluation sets derived from eQTL, activity-by-contact, CRISPR and genome-wide association study (GWAS) data. We further determined that restricting pgBoost to features from a focal cell type improved power to identify links relevant to that cell type. We highlight several examples in which pgBoost linked fine-mapped GWAS variants to experimentally validated or biologically plausible target genes that were not implicated by other methods. In conclusion, a non-linear combination of linking strategies improves power to identify target genes underlying GWAS associations.

PMID:40506539 | DOI:10.1038/s41588-025-02220-3

Br J Cancer. 2025 Jun 12. doi: 10.1038/s41416-025-03083-5. Online ahead of print.

ABSTRACT

BACKGROUND: Treatment of advanced estrogen receptor-positive HER-2-negative breast cancer is based on hormonal therapy with aromatase inhibitors for postmenopausal women. However, acquired endocrine resistance is unavoidable at some point in the advanced or metastatic stage, and its underlying molecular mechanisms remain to be fully elucidated. The study prospectively included patients with advanced or metastatic breast cancer who had relapsed or progressed following treatment with a non-steroidal aromatase inhibitor (AI) and were treated with exemestane (a steroidal AI) and everolimus. The objective was to perform DNA and RNA analyses in order to gain a deeper understanding of the genomic and transcriptomic landscape of endocrine-resistant advanced BC.

MATERIAL AND METHODS: We selected 65 patients included between 2015 and 2018 in the SAFIRTOR trial (NCT02444390). NGS-based gene panel of 65 genes (SAFIR02 core panel), Comparative genomic hybridization array and RNA-sequencing assessed single nucleotide variations, copy-number variations and gene expression and fusion genes of interest, respectively.

RESULTS: The most prevalent genomic alteration was ESR1, observed in 49% (32/65) of cases, with most being activating missense mutations. Two cases of ESR1 fusions were identified. The observed alterations were not mutually exclusive with those from NF1 or ERBB2. Differential expression analysis in the presence or absence of ESR1 alterations showed significant enrichment of the ESR-mediated signaling pathway in tumors with ESR1 alterations (p < 0.005). 17 genes were identified as significantly differentially expressed, forming a transcriptional signature with 81.3% sensitivity and 84.3% specificity (p < 0.0001). The oxidative phosphorylation (OXPHOS) pathway was significantly associated with resistance to everolimus (p = 5.05 × 10-10). 16 genes were differentially expressed between responders and non-responders, forming a OXPHOS gene signature distinguishing two groups with markedly different outcomes.

PMID:40506517 | DOI:10.1038/s41416-025-03083-5

Nat Plants. 2025 Jun 12. doi: 10.1038/s41477-025-02007-8. Online ahead of print.

ABSTRACT

Regulatory elements are essential components of plant genomes that have shaped the domestication and improvement of modern crops. However, their identity, function and diversity remain poorly characterized, limiting our ability to harness their full power for agricultural advances using induced or natural variation. Here we mapped transcription factor (TF) binding for 200 TFs from 30 families in two distinct maize inbred lines historically used in maize breeding. TF binding comparison revealed widespread differences between inbreds, driven largely by structural variation, that correlated with gene expression changes and explained complex quantitative trait loci such as Vgt1, an important determinant of flowering time, and DICE, an herbivore resistance enhancer. CRISPR-Cas9 editing of TF binding regions validated the function and structure of regulatory regions at various loci controlling plant architecture and biotic resistance. Our maize TF binding catalogue identifies functional regulatory regions and enables collective and comparative analysis, highlighting its value for agricultural improvement.

PMID:40506505 | DOI:10.1038/s41477-025-02007-8

Commun Biol. 2025 Jun 12;8(1):922. doi: 10.1038/s42003-025-08252-z.

ABSTRACT

IgGs have become successful drug scaffolds by combining specific target binding with the ability to induce cellular cytotoxicity. Furthermore, IgGs possess unusually long half-lives in the blood (2-3 weeks). IgGs achieve such extraordinary half-lives through a pH-dependent interaction with the FcRn-receptor whereby IgGs are recycled. No high-resolution structure of FcRn in complex with a full-length IgG is available, and the interaction was long thought to be mediated solely via the IgG-Fc. However, some IgGs with identical Fc-parts, but different Fab-domains, exhibit different half-lives, suggesting involvement of the Fab-domains in FcRn binding. Here, we employ structural mass spectrometry (HDX-MS and XL-MS) to explore the interaction of full-length IgGs with FcRn. HDX-MS and XL-MS experiments confirm an interaction between FcRn and the Fc-region of IgGs, through three cross-links between FcRn and the IgG-Fc-domain and a reduction in HDX in both the receptor and the Fc-region upon complex formation. However, FcRn-induced changes in HDX are also observed in the Fab-domains, supported by cross-links between the Fab-domains and the α3-domain of FcRn. Our results thus provide direct evidence for an IgG Fab-FcRn interaction. We envision that these results could advance the engineering of IgG-antibodies with tailored pharmacokinetics and enhanced efficacy.

PMID:40506471 | DOI:10.1038/s42003-025-08252-z

Nat Commun. 2025 Jun 12;16(1):5305. doi: 10.1038/s41467-025-60210-9.

ABSTRACT

One of the key achievements of equilibrium polymer physics is the prediction of scaling laws governing the viscoelastic properties of entangled polymer systems, validated in both natural polymers, such as DNA, and synthetic polymers, including polyethylene, which form materials like plastics. Recently, focus has shifted to active polymers systems composed of motile units driven far from equilibrium, such as California blackworms, self-propelled biopolymers, and soft robotic grippers. Despite their growing importance, we do not yet understand their viscoelastic properties and universal scaling laws. Here, we use Brownian dynamics simulations to investigate the viscoelastic properties of highly-entangled, flexible self-propelled polymers. Our results demonstrate that activity enhances the elasticity by orders of magnitude due to the emergence of grip forces at entanglement points, leading to its scaling with polymer length ∼ L. Furthermore, activity fluidizes the suspension, with the long-time viscosity scaling as ∼ L2, compared to ∼ L3 in passive systems. These insights open new avenues for designing activity-responsive polymeric materials.

PMID:40506452 | DOI:10.1038/s41467-025-60210-9

Cancer Lett. 2025 Jun 10:217867. doi: 10.1016/j.canlet.2025.217867. Online ahead of print.

ABSTRACT

Metastasis is the leading cause of death in patients with malignant melanoma, yet the molecular and transcriptional mechanisms remain elusive. This study reveals a crucial role of the p53 homolog, TAp73α, in promoting melanoma metastasis. Using multi-omics approaches combining transcriptomics, proteomics, cistromics and 3D modeling, we discovered a paradigm-shifting mechanism by which TAp73α binds directly to HDAC2, disassembles the HDAC2/REST repressor complex and aberrantly triggers activation of the neuronal receptor GABBR2 in cancer cells. TAp73α-induced derepression of GABBR2 expression leads to upregulation of EMT markers, promotes cancer cell invasiveness and proliferation, and correlates with poor survival outcomes. Our findings redefine the function of p73 in cancer pathogenesis and identify the TAp73α-HDAC2/REST-GABBR2 axis as a novel driver of melanoma progression. These insights could guide future strategies on melanoma treatment.

PMID:40505831 | DOI:10.1016/j.canlet.2025.217867

Metab Eng. 2025 Jun 10:S1096-7176(25)00088-6. doi: 10.1016/j.ymben.2025.06.002. Online ahead of print.

ABSTRACT

Bacillus methanolicus is the next workhorse in biotechnology using methanol, an alternative and economical one-carbon feedstock that can be obtained directly from carbon dioxide, as both carbon and energy source for the production of value-added chemicals. The wild-type strain B. methanolicus MGA3 naturally overproduces l-glutamate in methanol-based fed-batch fermentations. Here we generated a B. methanolicus strain exhibiting enhanced l-glutamate production capability through induced mutagenesis. To showcase the potential of this mutant strain, further metabolic engineering enabled the production of γ-aminobutyric acid (GABA) directly from l-glutamate during methanol fed-batch fermentations. Using a systems-level analysis, encompassing whole-genome sequencing, RNA sequencing, fluxome analysis and genome-scale metabolic modelling, we were able to elucidate the metabolic and regulatory adaptations that sustain the biosynthesis of these products. The metabolism of the mutant strain specifically evolved to prioritize energy conservation and efficient carbon utilization, culminating in increased product formation. These results and insights provide a foundation for further rational metabolic engineering and bioprocess optimization, enhancing the industrial viability of B. methanolicus for sustainable production of l-glutamate and its derivatives.

PMID:40505769 | DOI:10.1016/j.ymben.2025.06.002

Biotechnol Adv. 2025 Jun 10:108624. doi: 10.1016/j.biotechadv.2025.108624. Online ahead of print.

ABSTRACT

Lignin, the most abundant aromatic biopolymer on Earth, holds immense potential as a renewable feedstock for the production of high-value bioproducts. However, its structural complexity and recalcitrance pose significant challenges for efficient valorization. Fungal biodegradation offers a sustainable strategy for lignin conversion by employing extracellular oxidative enzymes and specialized metabolic pathways to transform lignin-derived aromatic compounds into central metabolites or valuable end products. Despite extensive research on fungal ligninolytic systems, a systematic integration of aromatic catabolic pathways remains fragmented. This review consolidates recent advances in fungal metabolism of key lignin-derived aromatics, including cinnamic acid, gallic acid, ferulic acid and vanillin, with a focus on their assimilation into central metabolic networks and the enzymatic machinery involved. We highlight the critical role of fungal transporter systems in mediating aromatic compound uptake and efflux. Furthermore, we discuss future research directions, emphasizing the integration of synthetic biology, computational modeling, and systems biology to engineer robust fungal chassis for lignin valorization. Addressing these knowledge gaps will advance the development of fungal-based platforms for sustainable production of renewable aromatics, thereby contributing to the circular bioeconomy and green biomanufacturing.

PMID:40505753 | DOI:10.1016/j.biotechadv.2025.108624

Cell Chem Biol. 2025 Jun 6:S2451-9456(25)00169-2. doi: 10.1016/j.chembiol.2025.05.008. Online ahead of print.

ABSTRACT

Fungal phytopathogens are responsible for major losses in agricultural yields annually. While the use of topical fungicides remains key to managing agricultural pathogens, the emergence of drug-resistant strains necessitates identifying additional treatment options. In this study, we performed an in vitro small molecule screen against the devastating cereal pathogen Fusarium graminearum, identifying CMLD009688 as a priority growth inhibitor. Chemical-genetic profiling and subsequent experiments with CMLD009688 revealed that this compound functions as a cationic amphiphilic drug (CAD) and perturbs vacuolar integrity in F. graminearum. CMLD009688 displayed synergy with strobilurin fungicides in limiting F. graminearum growth-likely through both compounds independently affecting vacuolar stability-and a combination treatment of CMLD009688 with the strobilurin pyraclostrobin strongly limited the virulence of both F. graminearum and Botrytis cinerea in distinct models of plant infection. Thus, our findings highlight that cationic amphiphilic molecules show immense promise in helping to protect crops from fungal diseases.

PMID:40505661 | DOI:10.1016/j.chembiol.2025.05.008

EBioMedicine. 2025 Jun 11;117:105798. doi: 10.1016/j.ebiom.2025.105798. Online ahead of print.

NO ABSTRACT

PMID:40505418 | DOI:10.1016/j.ebiom.2025.105798

J Pharmacol Exp Ther. 2025 May 19;392(7):103609. doi: 10.1016/j.jpet.2025.103609. Online ahead of print.

ABSTRACT

Chronic kidney disease (CKD) is a progressive ailment identified by renal fibrosis, inflammation, and mitochondrial dysfunction, necessitating the development of novel therapeutic interventions. Bifendate (dimethyl diphenyl bicarboxylate [DDB]), a known hepatoprotective agent, has shown promising antifibrotic properties, but its potential in CKD remains unexplored. This study integrates computational pharmacology, molecular docking, and experimental validation to explicate the mechanisms of renoprotection by DDB. Curative targets for CKD and DDB were identified from DisGeNET, GeneCards, and SwissTargetPrediction. Potential DDB targets against CKD were analyzed via STRING for protein interactions. Gene ontology and pathway enrichment (Database for Annotation, Visualization, and Integrated Discovery and Kyoto Encyclopedia of Genes and Genomes) were conducted, followed by network construction and analysis using Cytoscape (Institute for Systems Biology, USA). Network analysis identified 89 overlapping targets between DDB and CKD, including key regulators such as NF-κB1, PTGS2, and PPARG, which were enriched in multiple pathways, including calcium, Ras, ROS, NF-κB, and cAMP signaling. To validate these findings, a unilateral ureteral obstruction model in Sprague-Dawley rats was employed. DDB administration significantly mitigated kidney fibrosis, improved renal function markers, and preserved kidney morphology. Histological analyses confirmed that DDB attenuated tubular injury, glomerulosclerosis, and excessive collagen deposition. Furthermore, immunohistochemical assessments demonstrated that DDB suppressed epithelial-mesenchymal transition by restoring E-cadherin and reducing α-smooth muscle actin expression. Mitochondrial biogenesis was enhanced through PGC-1α upregulation, while inflammatory responses were dampened via NF-κB pathway inhibition. These findings highlight DDB's multifaceted therapeutic potential in CKD, acting through fibrosis inhibition, mitochondrial protection, and anti-inflammatory mechanisms. This study provides a strong foundation for further clinical investigations into DDB as a potential treatment for CKD, offering new insights into its mechanistic pathways. SIGNIFICANCE STATEMENT: This study demonstrates bifendate's therapeutic potential for chronic kidney disease through network pharmacology, identifying 89 common targets. Experimental validation in a unilateral ureteral obstruction model confirmed its renoprotective effects, revealing multi-target mechanisms against renal fibrosis and injury.

PMID:40505415 | DOI:10.1016/j.jpet.2025.103609

Science. 2025 Jun 12;388(6752):eadu1058. doi: 10.1126/science.adu1058. Epub 2025 Jun 12.

ABSTRACT

Quantitatively mapping enzyme sequence-catalysis landscapes remains a critical challenge in understanding enzyme function, evolution, and design. In this study, we leveraged emerging microfluidic technology to measure catalytic constants-kcat and KM-for hundreds of diverse orthologs and mutants of adenylate kinase (ADK). We dissected this sequence-catalysis landscape's topology, navigability, and mechanistic underpinnings, revealing catalytically heterogeneous neighborhoods organized by domain architecture. These results challenge long-standing hypotheses in enzyme adaptation, demonstrating that thermophilic enzymes are not universally slower than their mesophilic counterparts. Semisupervised models that combine our data with the rich sequence representations from large protein language models predict orthologous ADK-sequence catalytic parameters better than existing approaches. Our work demonstrates a promising strategy for dissecting sequence-catalysis landscapes across enzymatic evolution, opening previously unexplored avenues for enzyme engineering and functional prediction.

PMID:40504906 | DOI:10.1126/science.adu1058

PLoS Biol. 2025 Jun 12;23(6):e3003198. doi: 10.1371/journal.pbio.3003198. eCollection 2025 Jun.

ABSTRACT

Understanding synaptic dynamics during the sleep-wake cycle in the cortex is crucial yet remains controversial. The synaptic homeostasis hypothesis (SHY) suggests synaptic depression during non-rapid eye movement (NREM) sleep, while other studies report synaptic potentiation or synaptic changes during NREM sleep depending on activities in wakefulness. To find boundary conditions between these contradictory observations, we focused on learning rules and firing patterns that contribute to the synaptic dynamics. Using computational models considering mammalian cortical neurons, we found that under Hebbian and spike-timing dependent plasticity (STDP), wake-like firing patterns decrease synaptic weights, while sleep-like patterns strengthen synaptic weights. We refer to this tendency as Wake Inhibition and Sleep Excitation (WISE). Conversely, under Anti-Hebbian and Anti-STDP, synaptic depression during NREM sleep was observed, aligning with the conventional synaptic homeostasis hypothesis. Moreover, synaptic changes depended on firing rate differences between NREM sleep and wakefulness. We provide a unified framework that could explain synaptic homeodynamics under the sleep-wake cycle.

PMID:40504782 | DOI:10.1371/journal.pbio.3003198

Gigascience. 2025 Jan 6;14:giaf057. doi: 10.1093/gigascience/giaf057.

ABSTRACT

Since the late 2010s, artificial intelligence (AI), encompassing machine learning and propelled by deep learning, has transformed life science research. It has become a crucial tool for advancing the computational analysis of biological processes, the discovery of natural products, and the study of ecosystem dynamics. This review explores how the rapid increase in high-throughput omics data acquisition has driven the need for AI-based analysis in life sciences, with a particular focus on plant sciences, animal sciences, and microbiology. We highlight the role of omics-based predictive analytics in systems biology and innovative AI-based analytical approaches for gaining deeper insights into complex biological systems. Finally, we discuss the importance of FAIR (findable, accessible, interoperable, reusable) principles for omics data, as well as the future challenges and opportunities presented by the increasing use of AI in life sciences.

PMID:40504538 | DOI:10.1093/gigascience/giaf057

J Math Biol. 2025 Jun 12;91(1):11. doi: 10.1007/s00285-025-02235-8.

ABSTRACT

Asynchronous Boolean networks are a type of discrete dynamical system in which each variable can take one of two states, and a single variable state is updated in each time step according to pre-selected rules. Boolean networks are popular in systems biology due to their ability to model long-term biological phenotypes within a qualitative, predictive framework. Boolean networks model phenotypes as attractors, which are closely linked to minimal trap spaces (inescapable hypercubes in the system's state space). In biological applications, attractors and minimal trap spaces are typically in one-to-one correspondence. However, this correspondence is not guaranteed: motif-avoidant attractors (MAAs) that lie outside minimal trap spaces are possible. MAAs are rare and poorly understood, despite recent efforts. In this contribution to the BMB & JMB Special Collection "Problems, Progress and Perspectives in Mathematical and Computational Biology", we summarize the current state of knowledge regarding MAAs and present several novel observations regarding their response to node deletion reductions and linear extensions of edges. We conduct large-scale computational studies on an ensemble of 14 000 models derived from published Boolean models of biological systems, and more than 100 million Random Boolean Networks. Our findings quantify the rarity of MAAs; in particular, we only observed MAAs in biological models after applying standard simplification methods, highlighting the role of network reduction in introducing MAAs into the dynamics. We also show that MAAs are fragile to linear extensions: in sparse networks, even a single linear node can disrupt virtually all MAAs. Motivated by this observation, we improve the upper bound on the number of delays needed to disrupt a motif-avoidant attractor.

PMID:40504255 | DOI:10.1007/s00285-025-02235-8

Plant Dis. 2025 Jun 12. doi: 10.1094/PDIS-02-25-0432-RE. Online ahead of print.

ABSTRACT

Colletotrichum species are important fungal plant pathogens associated with citrus pre- or post-harvest disease globally. Seventy-three Colletotrichum isolates were collected from diseased leaves, fruits and twigs of lime, tangerine and pomelo in the provinces of Chiang Mai, Nakhon Pathom and Lampang in Thailand. Colletotrichum siamense, C. gloeosporioides, C. fructicola, C. gigasporum, C. kokhaense sp. nov., C. plurivorum and C. tropicicola were identified using morphological characters and multi-gene phylogenetic analysis (combinations of ITS, gapdh, ApMat, gs, tub2, act and his3 depending on the species complex). Colletotrichum siamense was the most prevalent species in Thailand, C. gigasporum was reported for the first time as a pathogen of citrus globally and the new species C. kokhaense in the magnum species complex was described. Pathogenicity tests confirmed that C. siamense, C. gloeosporioides, C. gigasporum, C. kokhaense sp. nov. and C. plurivorum were pathogenic to citrus fruits, seedlings and in planta shoots, with C. gigasporum being the most aggressive species. The non-wound inoculation technique provided good discrimination between high and low aggressive species compared to wound inoculation where most species appeared to be very aggressive. Knowledge of Colletotrichum species causing citrus disease and their pathogenic ability will assist the development of effective disease management strategies.

PMID:40504229 | DOI:10.1094/PDIS-02-25-0432-RE

J Integr Plant Biol. 2025 Jun 12. doi: 10.1111/jipb.13944. Online ahead of print.

ABSTRACT

In recent decades, research on model organisms has significantly increased our understanding of core biological processes in plant science. However, this focus has created a substantial knowledge bottleneck due to the limited phylogenetic and ecological spectrum covered. Gymnosperms, especially conifers, represent a molecular and ecological diversity hotspot among seed plants. Despite their importance, research on these species is notably underrepresented, primarily due to a slower pace of investigation resulting from a lack of community-based resources and databases. To fill this gap, we developed the P(inus)ra(diata)-G(ene)E(xpression) (Pra-GE)-ATLAS, which consists of several tools and two main modules: transcriptomics and proteomics, presented in this work for the forestry commercial and stress-sensitive species Pinus radiata. We have summarized and centralized all the available information to provide a comprehensive view of the gene expression landscape. To illustrate how applications of the database lead to new biological insights, we have integrated multiple regulatory layers across tissues and stressors. While stress favors the retention of small introns, harmonized alternative splicing analyses reveal that genes with conifers' iconic large introns tend to be under constitutive regulation. Furthermore, the degree of convergence between stressors differed between regulatory layers, with proteomic responses remaining highly distinctive even through intergenerational memory tolerance. Overall, the Pra-GE-ATLAS aims to narrow the distance between angiosperms and gymnosperms resources, deepening our understanding of how characteristic pine features have evolved. Pra-GE-ATLAS DB is available at: http://pra-ge-atlas.valmei.es.

PMID:40504102 | DOI:10.1111/jipb.13944

Biotechnol Bioeng. 2025 Jun 12. doi: 10.1002/bit.70001. Online ahead of print.

ABSTRACT

Environmental pH plays a crucial role in microbial metabolism. Microorganisms adapt their metabolic strategies in response to different pH conditions, which must be carefully controlled in industrial production processes to achieve desired outcomes. However, the dynamic impact of pH on hierarchical utilization of mixed carbon sources remains poorly understood. In this study, we observed that Bacillus coagulans exhibited distinct carbon source consumption rates and lactate yields at different pH levels under mixed carbon sources. We employed dynamic simulation methods using an enzyme-constrained genome-scale metabolic model, combined with transcriptomic and metabolomic data, to investigate the metabolic differences at pH 5.5, 6.0, and 6.5 conditions. The results revealed the significant flux differences in the glycolysis pathway across the tested pH conditions. Predictions also indicated that pH changes altered energy demands. Integrating omics data further revealed that under pH 5.5 conditions, a higher proportion of carbon was allocated to the phosphoketolase pathway, which provides high ATP yield. This strategy helps meet the energy demand of energy-consuming reactions that could maintain intracellular pH stability under acid stress, such as the reactions in amino acid metabolism. Consequently, we observed increased acetate production and decreased lactate production. Additionally, different pH conditions triggered a global response involving multiple metabolic pathways.

PMID:40503922 | DOI:10.1002/bit.70001

J Proteome Res. 2025 Jun 12. doi: 10.1021/acs.jproteome.5c00167. Online ahead of print.

ABSTRACT

One aim of the international Human Proteome Organization (HUPO) Human Proteome Project (HPP) is to obtain high-confidence translation evidence for every human protein-coding gene established in its target list of 19,433 entries based on the protein-coding genes from Ensembl-GENCODE. However, 76 are annotated in UniProtKB (as of release 2024_06) with PE5, indicating skepticism in the protein's existence from a manual curator, so it is unclear if these entries belong in the HPP target list. Here, we review these 76 entries by assembling evidence from the literature, reference databases, and genome alignments with other species to conclude whether these entries should be freed from their PE5 status to become annotated with PE1-4 in UniProtKB. We find that 17 of these have credible translation evidence and therefore should be upgraded to PE1. Another 15 lack translation evidence but have transcription evidence, the evolutionary hallmarks of protein-coding genes, and are presumed to produce functional proteins. 41 have no translational or transcriptional evidence, although they still bear the evolutionary hallmarks of protein-coding genes; currently, it remains unclear if these are protein-coding, so their representation becomes a matter of policy. Only 3 entries still seem best categorized as PE5 and excluded from the HUPO-HPP target list.

PMID:40503744 | DOI:10.1021/acs.jproteome.5c00167