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PubMed2026

Genomic determinants of fluoroquinolone resistance in Escherichia coli in Nigeria: dominance of QRDR mutations and limited contribution of PMQR in a cross-sectional study.

BACKGROUND: Fluoroquinolone-resistant Escherichia coli is a major global clinical threat, particularly in low- and middle-income countries like Nigeria. However, the full genomic landscape, including the relative contributions of chromosomal mutations, plasmid-mediated resistance, and the role of high-risk clones, remains poorly characterized in this setting. This study aimed to define the genomic mechanisms, clonal distribution, and genotype-phenotype relationships of fluoroquinolone resistance in clinical E. coli isolates from Nigeria. METHODS: A cross-sectional study of 107 clinical E. coli isolates was conducted. Phenotypic susceptibility to ciprofloxacin and nalidixic acid was determined using VITEK 2 and broth microdilution. Whole-genome sequencing was performed, and analysis included detection of quinolone resistance determining region (QRDR) mutations (gyrA, parC, parE) and plasmid-mediated quinolone resistance (PMQR) genes, multilocus sequence typing (MLST), and phylogenetic analysis. Statistical associations were evaluated using chi-squared tests or Fisher's exact tests. RESULTS: Ciprofloxacin non-susceptibility was high at 86.0%. Resistance was primarily driven by a conserved chromosomal mutation profile; the combination of gyrA S83L, gyrA D87N, and parC S80I was present in 85 isolates and was associated with ciprofloxacin non-susceptibility in all affected isolates in this cohort. Isolates with only gyrA mutations were resistant to nalidixic acid but susceptible to ciprofloxacin, consistent with a stepwise resistance pathway. In this cohort, the triple QRDR signature (gyrA S83L + gyrA D87N/Y + parC S80I) was a perfect positive predictor of ciprofloxacin non-susceptibility (85/85; 100%). The ST131 lineage dominated, accounting for 21.5% of isolates and universally carrying the complete triple QRDR profile; notably, no ST131 isolate carried a PMQR determinant. Plasmid-mediated quinolone resistance (PMQR) genes were detected in 15.0% of isolates but were not independently associated with ciprofloxacin non-susceptibility in this cohort in the absence of concomitant QRDR mutations. Efflux pump genes were ubiquitous and non-predictive. Notably, six isolates, all from urine, were non-susceptible (R/I) despite lacking all known QRDR and PMQR determinants, pointing to uncharacterized mechanisms. In a multivariable logistic regression model that included ST131 status, PMQR carriage, and parE mutation status, ST131 was associated with ciprofloxacin non-susceptibility (adjusted OR 5.96, 95% CI 1.21-29.4, p = 0.028), whereas PMQR carriage was not (adjusted OR 0.94, 95% CI 0.18-4.85, p = 0.94). The triple QRDR signature was not included in this model because it perfectly predicted ciprofloxacin non-susceptibility in this cohort. Resistance patterns varied by clinical source, with the highest burden in bloodstream and wound infections. This stepwise hierarchy from first-step gyrA mutations to the classic triple QRDR profile is summarised in the graphical abstract, Fig. 1. CONCLUSIONS: Fluoroquinolone resistance in Nigerian clinical E. coli is predominantly driven by chromosomal QRDR mutations within successful clones like ST131. PMQR genes and efflux pumps appeared to play a supplementary role rather than being independent drivers of ciprofloxacin resistance in this cohort. These data support prioritising key QRDR mutations in genomic reporting and local stewardship decisions, while the QRDR-negative resistant urine isolates require further investigation.

Escherichia coli↗

PubMed2024

The multifaceted role of mitochondria in cardiac function: insights and approaches.

Cardiovascular disease (CVD) remains a global economic burden even in the 21st century with 85% of deaths resulting from heart attacks. Despite efforts in reducing the risk factors, and enhancing pharmacotherapeutic strategies, challenges persist in early identification of disease progression and functional recovery of damaged hearts. Targeting mitochondrial dysfunction, a key player in the pathogenesis of CVD has been less successful due to its role in other coexisting diseases. Additionally, it is the only organelle with an agathokakological function that is a remedy and a poison for the cell. In this review, we describe the origins of cardiac mitochondria and the role of heteroplasmy and mitochondrial subpopulations namely the interfibrillar, subsarcolemmal, perinuclear, and intranuclear mitochondria in maintaining cardiac function and in disease-associated remodeling. The cumulative evidence of mitochondrial retrograde communication with the nucleus is addressed, highlighting the need to study the genotype-phenotype relationships of specific organelle functions with CVD by using approaches like genome-wide association study (GWAS). Finally, we discuss the practicality of computational methods combined with single-cell sequencing technologies to address the challenges of genetic screening in the identification of heteroplasmy and contributory genes towards CVD.

Humans↗

PubMed2026

Phylogeographic epidemiology of Dabie bandavirus in East Asia: divergent transmission networks and genotype‑linked clinical severity.

BACKGROUND: Severe fever with thrombocytopenia syndrome (SFTS), caused by Dabie bandavirus (SFTSV), exhibits geographically decoupled incidence and fatality patterns across East Asia. We aimed to elucidate the distinct ecological drivers and phylogeographic dynamics underlying this inland-coastal epidemiological divergence. METHODS: Integrating 1820 high-quality global genomes of SFTSV with well-characterized clinical cohorts (936 patients) and nationwide surveillance data (27,457 cases) from China, we constructed a comprehensive analytical framework. Ecological modeling, Bayesian phylogeography, and genotype-phenotype association analyses were employed to trace the evolutionary trajectories and clinical implications of the virus. RESULTS: A pronounced "inland-high-incidence vs. coastal-high-fatality" pattern of SFTS was identified. The incidence of SFTS exhibited divergent sensitivities to meteorological factors; inland transmission was sensitive to thermal fluctuations, whereas coastal dynamics were constrained by a sunshine threshold (> 200 h/month). In contrast, spatial divergence in clinical severity correlated with the distribution of regional viral genetic structures. Inland regions mainly co-circulated genotypes A, C, and D, while coastal regions were dominated by genotype B. Zhejiang province was identified as a genetic hub with significantly higher recombination frequencies than inland regions (11.0% vs. 3.5%, P < 0.001). Bayesian phylogeographic inference indicated frequent lineage exchange of Zhejiang province in China with the Republic of Korea and Japan. Clinically, genotypes B and D were associated with elevated mortality in coastal and inland regions, respectively, suggesting that the severe coastal phenotype is shaped by its genotype B-dominated structure. Additionally, the RdRp-N828S mutation emerged as a robust molecular correlate of fatal outcomes, warranting further functional validation. CONCLUSIONS: Divergent meteorological factors and plausible maritime transmission networks may underlie the geographically decoupled epidemiology of SFTS. These findings highlight that risk assessment must extend beyond incidence alone and provide a phylogeographically informed framework for targeted surveillance and genotype-specific interventions in high-risk hotspots.

Humans↗

PubMed2025

A spectral framework to map QTLs affecting joint differential networks of gene co-expression.

Studying the mechanisms underlying the genotype-phenotype association is crucial in genetics. Gene expression studies have deepened our understanding of the genotype  →  expression  →  phenotype mechanisms. However, traditional expression quantitative trait loci (eQTL) methods often overlook the critical role of gene co-expression networks in translating genotype into phenotype. This gap highlights the need for more powerful statistical methods to analyze genotype  →  network  →  phenotype mechanism. Here, we develop a network-based method, called spectral network quantitative trait loci analysis (snQTL), to map quantitative trait loci affecting gene co-expression networks. Our approach tests the association between genotypes and joint differential networks of gene co-expression via a tensor-based spectral statistics, thereby overcoming the ubiquitous multiple testing challenges in existing methods. We demonstrate the effectiveness of snQTL in the analysis of three-spined stickleback (Gasterosteus aculeatus) data. Compared to conventional methods, our method snQTL uncovers chromosomal regions affecting gene co-expression networks, including one strong candidate gene that would have been missed by traditional eQTL analyses. Our framework suggests the limitation of current approaches and offers a powerful network-based tool for functional loci discoveries.

Quantitative Trait Loci↗

PubMed2026

IBAS: Interaction-bridged association studies discovering novel genes underlying complex traits.

Genetic contributions to complex traits are often mediated through coordinated gene-gene interaction networks, yet most existing association frameworks focus on marginal single-gene effects and overlook higher-order dependency structures. Direct modeling of interactions remains challenging due to combinatorial complexity and statistical instability. We introduce Interaction-Bridged Association Study (IBAS), a general framework that incorporates pathway-level interaction patterns into genotype-phenotype association analysis without explicitly enumerating interactions. IBAS leverages transcriptomic reference data to construct low-dimensional representations of pathway activity, which guide SNP-weighting and gene-level association testing within a kernel-based framework. In perturbation-based simulations, IBAS demonstrates improved stability and reproducibility compared to conventional TWAS and gene-based methods, while maintaining well-calibrated Type I error under phenotype permutation. Application to the WTCCC datasets identifies both known and novel genes across multiple complex diseases, including candidates with modest marginal effects missed by standard approaches. These findings are supported by replication in an independent cohort, and analyses across multiple reference tissues revealing both shared and tissue-specific signals. Overall, IBAS provides a statistically robust and computationally tractable framework for incorporating interaction effects into association mapping, extending beyond the single-gene paradigm and enabling more comprehensive characterization of complex trait. IBAS is available on GitHub at: https://github.com/QingrunZhangLab/IBAS.

Polymorphism, Single Nucleotide↗

PubMed1992

Biological complexity and strategies for finding DNA variations responsible for inter-individual variation in risk of a common chronic disease, coronary artery disease.

Most common chronic diseases of humans aggregate, but do not segregate, in families. The segregation-linkage research paradigm has not provided great insights into their genetic etiology. In this paper, using coronary artery disease as an example, we discuss hierarchical organization, coherence, emergent properties and dynamism as features that characterize the complexity of genotype-phenotype relationships. We summarize a research strategy for evaluating the contribution of genetic and environmental factors to the prediction of inter-individual variation in risk of disease. We then review a statistical strategy that employs cladistic theory to identify individuals carrying mutant DNA sequences responsible for an observed association between marker variation in a gene and inter-individual variation in biological traits that determine risk of a common multifactorial disease. Finding these DNA sequences is a necessary step in our search for an understanding of the nature of the mapping of genetic variation into variation in risk of a disease like coronary artery disease.

Coronary Disease↗

PubMed2026

Familial short stature: genetic architecture, risk stratification, and precision management.

BACKGROUND: Familial short stature (FSS) has traditionally been considered a benign growth pattern characterized by short stature clustering within families and has often been regarded as a normal variant of growth. However, recent advances in genomic technologies have demonstrated that a subset of children presenting with an FSS phenotype harbor identifiable monogenic variants, particularly in genes involved in growth plate development and skeletal growth. These findings challenge the traditional phenotype-based understanding of FSS and support an etiology-oriented diagnostic framework. OBJECTIVE: To summarize current knowledge regarding the genetic architecture of FSS, review existing clinical risk stratification frameworks for genetic evaluation, and evaluate available evidence regarding treatment outcomes across different genetic etiologies. METHODS: A literature search was performed in PubMed, Embase, and Web of Science from inception to May 2026, using keywords including "familial short stature," "familial idiopathic short stature," "genetic testing," "ACAN," "SHOX," and "NPR2". Relevant original studies and review articles addressing genotype-phenotype correlations, diagnostic yield of genetic testing, or responses to recombinant human growth hormone (rhGH) therapy were considered. RESULTS: Emerging evidence indicates that monogenic variants can be identified in a subset of children with an FSS phenotype, especially among those with more severe short stature and autosomal dominant inheritance patterns. Variants affecting growth plate biology represent some of the most frequently reported genetic causes of FSS, with ACAN, SHOX, and NPR2 being the most frequently implicated genes. Existing clinical frameworks based on parental height patterns and inheritance characteristics may help stratify patients with FSS according to the likelihood of monogenic etiology and guide selection of individuals who may benefit from genetic testing. Available evidence suggests that rhGH therapy may improve growth outcomes in several monogenic forms of FSS, although treatment responses vary according to genetic etiology. CONCLUSIONS: FSS should be regarded as a heterogeneous clinical phenotype rather than a single diagnostic entity. Integration of existing clinical risk stratification approaches with molecular diagnosis may enable more precise identification of underlying genetic causes and facilitate individualized therapeutic decision-making. Future advances in FSS management will likely depend on precision medicine approaches linking phenotype, genotype, and treatment response.

Humans↗

PubMed2026

Stepwise Humanization of the Yeast TRAPP Core Enables Functional Analysis of TRAPP Variants.

The Transport Protein Particle (TRAPP) complex is a highly conserved multi-subunit tethering complex that plays a critical role in membrane trafficking. Mutations in TRAPP complex subunits have been implicated in a growing spectrum of rare genetic disorders, yet the molecular mechanisms underlying variant pathogenicity often remain unclear. Here, we developed a humanized yeast platform to enable systematic functional characterization of TRAPP complex variants of uncertain significance. Using a stepwise gene replacement strategy in Saccharomyces cerevisiae, we constructed a strain in which five yeast TRAPP core subunits were replaced with their human orthologues. The integration of human subunits was validated through quantitative RT-PCR and Western blotting. Growth assays revealed that partial humanization of the core complex recapitulates key functional aspects of TRAPP assembly and enables the functional investigation of variants of uncertain significance in vivo. Structural modeling and clash analysis provided insights into the impact of specific mutations on complex stability and subunit interactions. TRAPPC3 has not yet been definitively associated with human disease. Introduction of TRAPPC3 variants of uncertain clinical significance into the humanized strain resulted in pronounced growth defects and predicted structural clashes. This work demonstrates the power of humanized yeast as a model for elucidating potential genotype-phenotype relationships in TRAPPopathy disorders and provides a versatile platform to support variant interpretation, mechanistic studies, and potential therapeutic screening.

Saccharomyces cerevisiae↗

PubMed2026

Expanding the Genomic Spectrum of NHLRC2-Associated FINCA Disease: Integrated Bioinformatic Characterization of a Novel Deep Intronic Variant Predicted to Activate a Pseudoexon.

NHLRC2-associated FINCA disease is an ultra-rare autosomal recessive multisystem disorder caused by biallelic pathogenic variants in NHLRC2. Its mutational spectrum and genotype-phenotype correlations remain incompletely defined, and the contribution of non-coding variants is poorly understood. Here, we report a male infant with a severe FINCA-like phenotype, including early-onset hemolytic anemia, pulmonary involvement, neurodevelopmental impairment, growth failure, recurrent infections, and fatal progression at 8.5 months. Whole-genome sequencing identified a compound heterozygous NHLRC2 genotype comprising the previously reported pathogenic missense variant c.442G>T (p.Asp148Tyr) and a novel deep intronic variant, c.331+6863A>G. Segregation analysis confirmed inheritance from different parents. Integrated genomic and splicing analysis predicted that c.331+6863A>G creates a strong cryptic donor splice site and supports pseudoexon inclusion. Reconstruction of the predicted aberrant transcript indicated premature termination and potential susceptibility to nonsense-mediated mRNA decay. To our knowledge, this is the first reported deep intronic NHLRC2 variant predicted to activate pseudoexon inclusion. Although experimental validation was unavailable, convergent clinical, segregation, population, and computational evidence supports c.331+6863A>G as the most plausible second disease-associated allele. This case expands the genomic spectrum of NHLRC2-associated FINCA disease and highlights the diagnostic value of phenotype-driven whole-genome sequencing.

Humans↗

PubMed2026

From the Microscope to the Genome: A New Era in the Molecular Genetics of Epidermolysis Bullosa.

Epidermolysis bullosa (EB) is a heterogeneous group of inherited disorders characterised by skin fragility, caused by pathogenic variants in genes encoding structural components of the dermo-epidermal junction. With the advent of next-generation sequencing (NGS), the diagnostic paradigm has shifted from a morphological to a genotype-oriented approach. This review summarises the genetic architecture of EB, the types of mutations and genotype-phenotype relationships, the challenges in interpreting variants of unknown significance (VUS), and therapeutic strategies targeting specific mutational mechanisms, including read-through approaches, exon skipping and genome editing. The role of modifier genes and epigenetic factors in clinical variability is also discussed. The focus is on the translational potential of genomics for personalized therapy in EB. Overall, this review synthesizes the molecular basis of all four major EB types across 16+ classical genes, highlights the paradigm shift where NGS achieves a diagnostic yield exceeding 90%, and critically assesses recent therapeutic milestones-ranging from the first FDA-approved topical gene therapy to precision RNA and genome-editing modalities.

Humans↗

PubMed2026

Bridging Ancestry Gaps in Genomic Risk Prediction with Tabular Foundation Models.

MOTIVATION: Models deployed for genomic prediction of diseases perform unevenly across populations, limiting clinical utility. Two factors drive this limitation: large imbalances in sample availability across ancestry groups and non-stationarity of genotype-phenotype effect sizes across the ancestry continuum. While tabular foundation models with in-context learning (ICL) have shown strong sample efficiency in other domains, their effectiveness for genotype-to-phenotype prediction and their robustness to ancestry-driven effect heterogeneity remain unclear. RESULTS: Using large, ancestrally diverse biobank data, we show that ICL-capable tabular foundation models reduce performance degradation in under-sampled ancestry groups compared to conventional supervised approaches. However, we find that prevailing models trained on existing synthetic tabular tasks fail when allele effect sizes vary across ancestry space. Treating genetic ancestry as a continuous variable, we introduce an instruction-tuning framework that exposes models to synthetic tasks with ancestry-dependent non-stationary effects. Instruction-tuned models achieve improved and more stable predictive performance across the genetic ancestry continuum, including for individuals distant from in-context exemplars in ancestry space. AVAILABILITY AND IMPLEMENTATION: All code for instruction-tuning models, synthetic task generation, data wrangling, and model evaluation, is publicly available at https://github.com/ai4pm/Bridging-Ancestry-Gaps-in-Genomic-Risk-Prediction-with-Tabular-Foundation-Models. The final instruction-tuned model (ICL-NS-G2P-proto) is also released in this repository. Detailed documentation is provided, including environment setup instructions and guidelines for running various parts. The instruction-tuning task datasets are available at https://zenodo.org/records/18309187.

Ancestry Continuum↗

PubMed1992

The cystic fibrosis gene and relationships to clinical status.

Cystic fibrosis (CF) is a disease characterized by significant variability in both presentation and clinical course. The genetic and environmental factors responsible for the phenotypic expression of CF are most likely legion, and their relationship to the disease complex. Therefore, it was not until the isolation and characterization of the CF gene and the ability to genotype individual patients that further elucidation of the genotype-phenotype relationship in CF was possible. Currently, the pancreatic status of CF patients appears to be primarily determined by genetic factors and patients homozygous for the most common mutation, delta F508 are, as a rule, pancreatic insufficient. Other specific alleles that confer pancreatic sufficiency have been identified. Patients having these alternative alleles remain pancreatic sufficient, are diagnosed later, have lower sweat chloride values, milder respiratory disease, and a better prognosis than patients with alleles associated with pancreatic insufficiency. Other clinical manifestations, including meconium ileus and the presence of liver disease, appear to be associated with pancreatic insufficiency. The variability in the pulmonary course for homozygous delta F508 patients suggests that genetic heterogeneity at other loci or environmental factors are important. Therefore, the CF genotype does not precisely predict pulmonary status.

Chromosomes, Human, Pair 7↗

PubMed1992

[Retinitis pigmentosa. Clinical findings, results of molecular genetic techniques and research perspectives].

In recent years, research efforts in the basic and clinical sciences have yielded numerous new findings. The review given here outlines clinical findings, research results, and perspectives on the origin of hereditary retinal degeneration as far as molecular genetics, biochemistry, morphology, and clinical research are concerned: genotype-phenotype correlation, electroretinography, color perimetry, blue cone function, exogenous factors, refraction problems, fat metabolism, immunological aspects, retinal transplantation, and phenocopies of retinitis pigmentosa and related syndromes. The consequences for ophthalmological practice are pointed out and comprehensive, improved diagnostic procedures are recommended, using a checklist proposed here (see appendix).

Adult↗

PubMed1992

[Current views of thalassemia intermedia].

Recently the molecular bases of thalassemia intermedia have been elucidated in several populations. In general this attenuated, non-transfusion dependent form of homozygous beta-thalassemia is mainly determined by a) the co-inheritance of deletion alpha-thalassemia; b) the presence of the so-called mild beta-thalassemia mutations; and more rarely, c) the inheritance of genetic conditions able to enhance the gamma-globin chain expression in adult life. Although there are several complex genetic and acquired interactions involved in the wide clinical heterogeneity of thalassemia intermedia, data in Italians indicate a definite genotype-phenotype relationship in conditions such as the co-inheritance of at least two alpha-thalassemia genes in severe and mild homozygous beta-thalassemia; the molecular homozygosity or double heterozygosity for the -87, -101 and IVS1(nt6) beta(+)-thalassemia mutations; and the coexistence of structural gamma-globin gene defects, i.e. Sicilian and Sardinian delta beta-thalassemias, deletional and non-deletional hereditary persistence of fetal hemoglobin and the polymorphism for the -158 XmnI G gamma restriction site. Thalassemia intermedia resulting from the inheritance in heterozygous beta-thalassemia of triple alpha-globin gene complex or the presence of dominant beta-thalassemia is also described and the role of these new informations in genetic counselling is discussed.

Base Sequence↗

PubMed1992

Short stature in a girl with a terminal Xp deletion distal to DXYS15: localisation of a growth gene(s) in the pseudoautosomal region.

This report describes a Japanese girl with short stature and a rearranged X chromosome. Her height remained below the 3rd centile growth curve for Japanese girls, and her predicted adult height (148.5 cm) was below her target height (163 cm) and target range (155 to 171 cm). Cytogenetic studies showed that the rearranged X chromosome was formed by a breakage at q26 and a transfer of the Xq fragment onto the tip of Xp. The abnormal X was always late replicating. No mosaicism was detected. Molecular analysis showed an Xp terminal deletion distal to DXYS15. Biochemical and radiological studies for short stature disclosed no abnormality. On the basis of height analysis of previous reports and a genotype-phenotype correlation of this patient, we propose that a growth gene(s) is present in the distal part of the pseudoautosomal region.

Blotting, Southern↗

PubMed1991

Human beta-galactosidase gene mutations in GM1-gangliosidosis: a common mutation among Japanese adult/chronic cases.

Molecular analysis of the human beta-galactosidase gene revealed six different mutations in 10 of 11 Japanese GM1-gangliosidosis patients. They were the only abnormalities in each allele examined in this study. A 165-nucleotide duplication (positions 1103-1267) was found in two infantile patients, producing an abnormally large mRNA; one patient was probably a homozygote, and the other was a heterozygote of this mutation. The other two infantile patients had different mutations; a 123 Gly(GGG)----Arg(AGG) mutation in one patient and a 316 Tyr(TAT)----Cys(TGT) mutation in the other. A 201 Arg(CGC)----Cys(TGC) mutation, eliminating a BspMI site, was detected in a late-infantile/juvenile patient; the restriction-site analysis of amplified genomic DNA confirmed his heterozygosity for this mutation. A 51 Ile(ATC)----Thr(ACC) mutation was found in all five adult/chronic patients examined in this study. It created a SauI site, and restriction-site analysis confirmed that four patients were homozygous mutants. The other was a compound heterozygote for this mutation and another 457 Arg(CGA)----Gln(CAA) mutation. These mutant genes expressed markedly decreased or completely deficient enzyme activities in beta-galactosidase-deficient human fibroblasts transformed by adenovirus-SV40 recombinants. We conclude that gene mutations are heterogeneous in GM1-gangliosidosis but that the 51 Ile(ATC)----Thr(ACC) mutation is common among the Japanese adult/chronic cases. Genotype-phenotype correlations in GM1-gangliosidosis are briefly discussed.

Adolescent↗

PubMed1991

Single-strand conformation polymorphism for detection of mutations and base substitutions in phenylketonuria.

In the past few years, more than 20 different mutations have been reported in hyperphenylalaninemias. In southwestern Europe and Mediterranean countries, however, the mutant genotypes reported account for only a fraction (27%) of all mutant alleles at the phenylalanine hydroxylase (PAH) locus, and most of the mutations causing the disease remain unknown. In order to develop a strategy for rapid detection of mutation-containing exons, we applied the single-strand conformation-polymorphism (SSCP) technique to exons 3, 5, 7, and 12 of the PAH gene. We observed five abnormal patterns of migration in mutant PAH genes, and we consistently found base substitutions in the corresponding exons, with no false-positive results. By this procedure, two novel putative mutations were detected in the seventh exon of the PAH gene, (A259V and Y277D) and we were able to demonstrate that the delta I94, R158Q, R408W, and E280K mutations were easily detectable by the SSCP technique. This procedure is therefore of particular interest for rapid detection of mutation-containing exons and for determination of further genotype-phenotype correlations in hyperphenylalaninemias.

Base Sequence↗

PubMed2026

Genome-based predictions of metabolic preferences and substrate phenotypes in psychrotrophic bacteria from permafrost environments.

Genomes reveal vast functional potential, but harbor genomic noise that obscures prediction of metabolic and environmental preferences. Genomic databases are skewed towards clinically relevant and easily cultivated bacteria, limiting predictions for diverse and underrepresented environmental taxa. Psychrotrophic bacteria, which can survive and grow in cold, nutrient-limited, dry, and saline environments, are especially underrepresented despite their relevance for understanding microbial responses to changing cold environments and potential biotechnological value given growth at low temperatures. Assembling complete genomes of 48 isolates from Alaskan permafrost, seasonally frozen active layer soils, and terrestrial ice, we used Kyoto Encyclopedia of Genes and Genomes (KEGG) ortholog annotations to evaluate the predictability of metabolic resource-use traits observed using phenotypic tests. Genome-predicted values for glycolytic versus gluconeogenic catabolic preference index, or sugar-acid preference (SAP), explained over 50% of the variance in empirically observed SAP. SAP was inversely correlated to genomic GC content, which follows phylum-level trends, indicating that coarse metabolic preference covaries with phylogeny. Regularized elastic net models offered a more granular view, linking KEGG genes to specific substrate utilization and sensitivity phenotypes and yielding moderate but reproducible accuracy (AUC 0.70-0.79) for 11 substrates, demonstrating that specific substrate responses may be predictable from relatively small subsets of KO genes. These results extend recent advances, such as the SAP metric, and highlight associations among genomic GC content, phylum, and broad metabolic strategy. Linking genomic content to phenotype using isolates is a necessary step toward predictive models of microbial function in environmental communities, and this work can be used for hypothesis generation, with applications towards more expansive data sets.IMPORTANCECold region soils and ice host psychrotrophic bacteria with metabolic traits and adaptations that enable persistence in harsh, resource-limited environments. However, these taxa are underrepresented in genomic reference databases dominated by well-studied, mesophilic organisms. This gap limits inference of ecological strategies and our ability to predict how these microbes may influence the large, thaw-vulnerable carbon reservoirs in permafrost. Here, we show that genomic GC content is associated with the sugar-versus-acid catabolic preference (SAP) of isolates across major phyla, suggesting that broad genomic features may provide a coarse signal of metabolic strategy. We demonstrate that a modified SAP metric, using binary (positive/negative) substrate utilization rather than detailed growth rate measurements, is moderately predictive, thus extending its application to slow-growing or difficult-to-culture taxa. Together, these advances broaden the toolkit for linking genome content to resource-use traits (phenotype) in poorly characterized, cold-adapted bacteria and offer a tractable entry point to broad prediction and hypothesis generation.

Genome, Bacterial↗