Genome Database Research Articles

Precision oncology platforms: practical strategies for genomic database utilization in cancer treatment.

In recent years, the expansion of molecularly targeted cancer therapies has significantly advanced precision oncology. Parallel developments in next-generation sequencing (NGS) technologies have also improved precision oncology applications, making genomic analysis of tumors more affordable and accessible. Targeted NGS panels now enable the rapid identification of diverse actionable mutations, requiring clinicians to efficiently assess the predictive value of cancer biomarkers for specific treatments. The urgency for timely and accurate decision-making in oncology emphasizes the importance of reliable precision oncology software. Online clinical decision-making tools and associated cancer databases have been designed by consolidating genomic data into standardized, accessible formats. These new platforms are highly integrated and crucial for identifying actionable somatic genomic biomarkers essential for tumor survival, determining corresponding drug targets, and selecting appropriate treatments based on the mutational profile of each patient's tumor. To help oncologists and translational cancer researchers unfamiliar with these tools, we review the utility, accuracy, and comprehensiveness of several commonly used precision medicine software options currently available. Our analysis categorized selected genomic databases based on their primary content, utility, and how well they provide practical guidance for interpreting somatic biomarker data. We identified several comprehensive, mostly open-access platforms that are easy to use for genetic biomarker searches, each with unique features and limitations. Among the precision oncology tools we evaluated, we found MyCancerGenome and OncoKB to be the first choice, offering comprehensive, accurate up-to-date information on the clinical significance of somatic mutations. To illustrate the application of these precision oncology tools in clinical settings, we evaluated three case studies to see how use of the platforms could have influenced treatment planning. Most of the precision oncology software evaluated could be easily streamlined into clinical workflows to provide updated information on approved drugs and clinical trials related the actionable mutations detected. Some platforms were very intuitive and easy to use, while others, often developed in smaller academic settings, were more difficult to navigate and may not be updated consistently. Future enhancements, incorporating artificial intelligence algorithms, are likely to improve integration of the platforms with diverse big data sources, enabling more accurate predictions of potential therapeutic responses.

Genomic Surveillance of Foodborne Pathogens: Advances and Obstacles

Context: The genomic surveillance of foodborne pathogens in the United States has grown exponentially in the past decade, grounded in a powerful combination of novel sequencing technologies, bioinformatic approaches, data-sharing networks, and metadata harmonization efforts. This practice report examines recent advances in genomic epidemiology as applied to food safety programs and delineates State, Tribal, Local, and Territorial infrastructure necessary for continued life-saving improvements in public health. Program: National databases of foodborne pathogen genomes, along with data sharing and evaluation networks such as GenomeTrakr and PulseNet, have transformed how connections are made among isolates and how root causes of outbreaks are determined, allowing much more timely interventions to protect public health. Freely available bioinformatics tools such as GalaxyTrakr and the National Center for Biotechnology Information Pathogen Detection database have allowed laboratories with limited local computing resources to participate in surveillance efforts and contribute to traceback investigations. Implementation: In this report, we describe advances in genomic epidemiology that have occurred over the past decade and examine obstacles to fully implementing this technology within State, Tribal, Local, and Territorial public health systems. Evaluation: Despite a clear return on investment from governmental expenditures on genomic surveillance of foodborne pathogens, we identify significant obstacles to further sustained progress. These obstacles include workforce gaps, ineffective data sharing, and lack of constitutive and sustained funding. Discussion: Many public health laboratories face major obstacles to widespread and routine adoption of genomic surveillance technologies. While whole genome sequencing has become an integral part of routine public health microbiology, the seamless integration of these protocols into the existing practices, laboratory workflows, and information systems remains challenging. Centralized efforts to address these issues include (1) support through the Food and Drug Administration Laboratory Flexible Funding Model, (2) training and proficiency assessments, (3) open-source, standardized protocols for collecting high-quality genomic data, and (4) open access informatics software.

Isolation and Characterization of Highly Lytic Bacteriophages against Staphylococcus aureus in Malaysian Sewage Water

Staphylococcus aureus is a pathogen that can cause both minor and life-threatening infection to human. Recently, the emergence of antibiotic-resistant Staphylococcus aureus (MRSA) has become a global public health concern. As an alternative to antibiotics, bacteriophage therapy is receiving increasing attention. Isolation and characterization of more Staphylococcus aureus phages is an important pre-requisite for building a large repository of phages that can be used in the future for phage therapy. Here we report the isolation of bacteriophages against S. aureus ATCC 6538, the first of its kind in Malaysia. Twenty phages were isolated and two were examined in detail. These two phages, TJSb3 and TJSb6, were found to be highly lytic and belong to the order Caudovirales and the family Siphoviridae. TJSb3 and TJSb6 have high efficiency of plating (EOP value) of 0.907 ± 0.085 and 0.665 ± 0.114, respectively. These two phages exhibited a broad lytic effect against the 4 different S. aureus strains tested (one of which, S. aureus ATCC 43300, is a MRSA strain). TJSb3 and TJSb6 also have small genome size of 20-30k base pairs, making them smaller than 90% of the S. aureus phages recorded in the NCBI viral genome database. These traits make TJSb3 and TJSb6 very attractive as potential candidates for phage therapy.

Saccharomyces Genome Database: Advances in Genome Annotation, Expanded Biochemical Pathways, and Other Key Enhancements.

Budding yeast (Saccharomyces cerevisiae) is the most extensively characterized eukaryotic model organism and has long been used to gain insight into the fundamentals of genetics, cellular biology, and the functions of specific genes and proteins. The Saccharomyces Genome Database (SGD) is a scientific resource that provides information about the genome and biology of S. cerevisiae. For more than 30 years, SGD has maintained the genetic nomenclature, chromosome maps, and functional annotation for budding yeast along with search and analysis tools to explore these data. Here we describe recent updates at SGD, including the two most recent reference genome annotation updates, expanded biochemical pathways representation, changes to SGD search and data files, and other enhancements to the SGD website and user interface. These activities are part of our continuing effort to promote insights gained from yeast to enable the discovery of functional relationships between sequence and gene products in fungi and higher eukaryotes.

MolluscDB 2.0: a comprehensive functional and evolutionary genomics database for over 1400 molluscan species.

Mollusca represents the second-largest animal phylum but remains less explored genomically. The increase in high-quality genomes and diverse functional genomic data holds great promise for advancing our understanding of molluscan biology and evolution. To address the opportunities and challenges facing the molluscan research community in managing vast multi-omics resources, we developed MolluscDB 2.0 (http://mgbase.qnlm.ac), which integrates extensive functional genomic data and offers user-friendly tools for multilevel integrative and comparative analyses. MolluscDB 2.0 covers 1450 species across all eight molluscan classes and compiles ∼4200 datasets, making it the most comprehensive multi-omics resource for molluscs to date. MolluscDB 2.0 expands the layers of multi-omics data, including genomes, bulk transcriptomes, single-cell transcriptomes, proteomes, epigenomes and metagenomes. MolluscDB 2.0 also more than doubles the number of functional modules and analytical tools, updating 14 original modules and introducing 20 new, specialized modules. Overall, MolluscDB 2.0 provides highly valuable, open-access multi-omics platform for the molluscan research community, expediting scientific discoveries and deepening our understanding of molluscan biology and evolution.

Identification of a coagulation-related gene signature for predicting prognosis in recurrent glioma.

Recurrent gliomas rapidly progress and have high mortality and poor prognosis in the central nervous system. Therefore, further investigation of prognostic and therapeutic markers is needed. The mRNA expression, clinical data, and coagulation-related genes (CRGs) associated with recurrent glioma were obtained and calculated from the Chinese Glioma Genome Atlas and Kyoto Encyclopedia of Genes and Genomes databases. The significant CRGs were calculated by Weighted gene co-expression network analysis and PPI network. A prediction model was constructed using the least absolute shrinkage and selection operator regression analysis. Recurrent gliomas were stratified into high and low-risk groups based on the median risk score (RS). The Kaplan-Meier curve was used to analyze the difference in overall survival (OS) between these groups, while the receiver operating characteristic (ROC) curve was used to evaluate the accuracy of the gene model at 1-, 3-, and 5-years. Clinical factors, including age, gender, MGMT methylation status, radiotherapy, chemotherapy, and RS, were included in the univariate and multivariate regression analysis. A prognostic nomogram and calibration curve were established based on these factors. Overall, seven CRGs associated with the prognosis were identified, including BTK, ITGB1, GNAI3, CFH, LYN, CFI, and F3. OS and survival rates were lower in the high-risk group compared with the low-risk group. The ROC curve demonstrated the area under the curve values >0.65 at 1-, 3-, and 5-years, confirming the reliability of the prognostic model. The univariate regression analysis indicated that tumor grade (grades 2, 3, and 4), histopathology (GBM or not), chemotherapy, IDH mutation, and 1p19q co-deletion status were independent prognostic indicators. Univariate and multivariate regression analyses indicated that RS was an independent prognostic factor for patients with recurrent glioma. Immune analysis revealed low infiltration of resting dendritic cells and high expression of programmed death receptor 1 in the high-risk group. This study comprehensively investigated the correlation between CRGs and recurrent glioma prognosis, offering crucial insights for further research into glioma recurrence mechanisms and treatment strategies.

BIOM-05. FUSION TRANSCRIPTOME LANDSCAPE IN GLIOBLASTOMA

Abstract BACKGROUND For most patients with glioblastoma (GBM), no truly effective salvage therapies exist. However, there are compelling examples in oncology where gene fusions lead to functioning oncoproteins that are highly effective targets (ie BCR-ABL1 in CML). Using a large genomic database, we sought to determine the prevalence of fusion transcripts in GBMs. METHODS A total of 4392 GBMs were tested at Caris Life Sciences (Phoenix, AZ). Mutations were detected by NextGen sequencing of DNA (592-gene panel or whole exome sequencing); gene fusions were detected by Whole Transcriptome Sequencing. All tumors were wild type for IDH1/2. Significance was tested by Fisher-Exact and ChiSquare and adjusted by Benjamini-Hochberg (q <0.05). RESULTS Overall, pathogenic fusions were found in 428 (9.7%). The most prevalent were FGFR3 [N=159 (37%), highest FGFR3:TACC3, N=134], MET [N=92 (21%), highest PTPRZ1:Met, N=31; ST7:MET N=25; CAPZA2: MET, N=23), EGFR [N=87(20%), highest EGFR:SETP14, N=21 and SEC61G: EGFR, N=19], NTRK2 (N=27), PDGFRA (N=23), ROS1 (N=14) and BRAF (N=10). Other actionable fusions including ALK (N=3), NTRK3 (N=3), RAF1(N=3), RET (N=3), NTRK1(N=2) were seen. Tumors with fusions were more likely to have pathogenic gene amplifications including: MET (7.5% vs. 0.7%), FGFR3 (5% vs. 0.2%), CDK4 (17% vs. 11%) and MDM2 (12% and 7.5%) but less frequent EGFR mutation (6.1% vs. 18%), amplification (6.1% vs. 18%) and EGFRvIII mutation (11.9% vs. 22.5%), RB1 (2.9% vs. 11.5%) and TP53mutation (22% vs. 30%) (all q<0.05). EGFR fusions are enriched with EGFR amplification (92%) and EGFRvIII mutation (51%); cMET fusion with MET amplification (40%). CONCLUSIONS Comprehensive molecular profiling reveals that approximately 10% of IDH WT GBMs carry oncogenic fusions that may be therapeutic targets. Broad spectrum of observed fusions underscores the need for novel clinical trial designs to allow efficient enrollment for prospective testing of potential targeted agents.

SoIR: a comprehensive Solanaceae information resource for comparative and functional genomic study.

The Solanaceae family, which includes economically important crops such as tomatoes, potatoes and peppers, has experienced a rapid expansion in genomic data due to advancements in sequencing technologies. However, existing databases are limited by incomplete species representation, a lack of comprehensive comparative genomic tools and the absence of systematic pan-genomic analyses. To address these gaps, we developed the Solanaceae Information Resource (SoIR, https://soir.bio2db.com), a comprehensive genomics database for the Solanaceae family. SoIR integrates genomic data from 81 species and transcriptomic data from 41 species, encompassing a total of 3908408 gene annotations derived from Gene Ontology, nonredundant protein, Pfam, Swiss-Prot and TrEMBL databases. The resource also includes 3437115 CRISPR guide sequences, 212395 transcription factorsand 19086 genes associated with methylation modification. In addition to species-specific analyses, SoIR provides extensive bioinformatics tools for investigating gene family evolution, phylogenetic relationships and karyotype reconstruction across 25 fully sequenced genomes. With advanced tools such as Blast, Synteny and Sequence Alignment, the platform provides users with interactive and intuitive visualizations for conducting cross-species comparative genomics. As the first comprehensive pan-genomic resource for the entire Solanaceae family, SoIR facilitates in-depth cross-species analysis, supporting global research initiatives in plant evolution, functional genomics and crop improvement.

GutMetaNet: an integrated database for exploring horizontal gene transfer and functional redundancy in the human gut microbiome.

Metagenomic studies have revealed the critical roles of complex microbial interactions, including horizontal gene transfer (HGT) and functional redundancy (FR), in shaping the gut microbiome's functional capacity and resilience. However, the lack of comprehensive data integration and systematic analysis approaches has limited the in-depth exploration of HGT and FR dynamics across large-scale gut microbiome datasets. To address this gap, we present GutMetaNet (https://gutmetanet.deepomics.org/), a first-of-its-kind database integrating extensive human gut microbiome data with comprehensive HGT and FR analyses. GutMetaNet contains 21567 human gut metagenome samples with whole-genome shotgun sequencing data related to various health conditions. Through systematic analysis, we have characterized the taxonomic profiles andFR profiles, and identified 14636 HGT events using a shared reference genome database across the collected samples. These HGT events have been curated into 8049 clusters, which are annotated with categorized mobile genetic elements, including transposons, prophages, integrative mobilizable elements, genomic islands, integrative conjugative elements and group II introns. Additionally, GutMetaNet incorporates automated analyses and visualizations for the HGT events and FR, serving as an efficient platform for in-depth exploration of the interactions among gut microbiome taxa and their implications for human health.

Genomic and Bioinformatics Analysis of Familial Partial Lipodystrophy Type 3 Identified in a Patient with Novel PPARγ Mutation and Robust Response to Pioglitazone

Familial partial lipodystrophies (FPLDs) are very rare inherited disorders characterized by partial loss of adipose tissue from the upper and lower extremities. At least seven subtypes of FPLD have been identified and are mostly dominantly inherited. FPLD type 3 is caused by mutations in the PPARγ gene, which encodes for the protein peroxisome proliferator-activated receptor gamma (PPARγ). We identified a Saudi female with PFLD3 presented with partial lipoatrophy, uncontrolled diabetes, severe hypertriglyceridemia, and recurrent pancreatitis. The clinical and biochemical findings in this proband were described before and after treatment with Pioglitazone in addition to the conventional treatment. DNA extraction and whole exome sequencing (WES) were performed to detect the variant. The mutant gene was subjected to Sanger analysis to confirm the results. We applied five specific computational prediction tools to assess the pathogenicity of variation, namely the MT, DANN, CADD, BayesDel, and fitCons tools. We assessed protein modeling and stability with the AlphaFold-generated structures for both wild-type and mutant proteins. Finally, we conducted molecular docking using the AutoDock Vina virtual docking. Upon whole exome sequencing, a c.1024C>T p.(Gln342Ter) missense mutation was detected in the PPARγ gene associated with FPLD3. This variant is a novel mutation that has not been described in all genome databases. Sanger analysis confirmed the heterogenicity and pathogenicity of this variant. All five computational prediction tools indicate that this variant is considered highly pathogenic. Our patient showed a dramatic response to Pioglitazone, a synthetic PPARγ agonist. From structural modeling, we found that the enhanced binding affinity of the mutant PPARγ protein to Pioglitazone likely improves the activation of PPARγ, enhancing its transcriptional activity and resulting in better clinical outcomes. These findings extend the spectrum of PPARγ mutations responsible for FPLD3 and highlight the potential for personalized treatment strategies based on genetic mutations.

Bioinformatic Multi-Strategy Profiling of Congenital Heart Defects for Molecular Mechanism Recognition

Congenital heart defects (CHDs) rank among the most common birth defects, presenting diverse phenotypes. Genetic and environmental factors are critical in molding the process of cardiogenesis. However, these factors’ interactions are not fully comprehended. Hence, this study aimed to identify and characterize differentially expressed genes involved in CHD development through bioinformatics pipelines. We analyzed experimental datasets available in genomic databases, using transcriptome, gene enrichment, and systems biology strategies. Network analysis based on genetic and phenotypic ontologies revealed that EP300, CALM3, and EGFR genes facilitate rapid information flow, while NOTCH1, TNNI3, and SMAD4 genes are significant mediators within the network. Differential gene expression (DGE) analysis identified 2513 genes across three study types, (1) Tetralogy of Fallot (ToF); (2) Hypoplastic Left Heart Syndrome (HLHS); and (3) Trisomy 21/CHD, with LYVE1, PLA2G2A, and SDR42E1 genes found in three of the six studies. Interaction networks between genes from ontology searches and the DGE analysis were evaluated, revealing interactions in ToF and HLHS groups, but none in Trisomy 21/CHD. Through enrichment analysis, we identified immune response and energy generation as some of the relevant ontologies. This integrative approach revealed genes not previously associated with CHD, along with their interactions and underlying biological processes.

Carrier Frequency and Incidence of MUTYH-Associated Polyposis Based on Database Analysis in East Asians and Koreans.

MUTYH-associated polyposis is an autosomal recessive disorder associated with an increased lifetime risk of colorectal cancer and a moderately increased risk of ovarian, bladder, breast, and endometrial cancers. We analyzed the carrier frequency and estimated the incidence of MUTYH-associated polyposis in East Asian and Korean populations, for which limited data were previously available. We examined 125,748 exomes from the gnomAD database, including 9,197 East Asians, and additional data from 5,305 individuals in the Korean Variant Archive and 1,722 in the Korean Reference Genome Database. All MUTYH variants were interpreted according to the American College of Medical Genetics and Genomics and Association for Molecular Pathology guidelines and the Sequence Variant Interpretation guidelines from ClinGen. The global carrier frequency of MUTYH-associated polyposis was 1.29%, with Europeans (non-Finnish) having the highest frequency of 1.86% and Ashkenazi Jews the lowest at 0.06%. East Asians and Koreans had a carrier frequency of 0.35% and 0.37% and an estimated incidence of 1 in 330,409 and 1 in 293,304 in Koreans, respectively, which were substantially lower than the global average of 1 in 24,160 and the European (non-Finnish) incidence of 1 in 11,520. This was the first study to investigate the frequency of carriers of MUTYH-associated polyposis in East Asians, including specific subgroups, utilizing gnomAD and a Korean genome database. Our data provide valuable reference information for future investigations of MUTYH-associated polyposis to understand the genetic diversity and specific variants associated with this condition in East Asian populations.

Removal of sequencing adapter contamination improves microbial genome databases

Advances in assembling microbial genomes have led to growth of reference genome databases, which have been transformative for applied and basic microbiome research. Here we show that published microbial genome databases from humans, mice, cows, pigs, fish, honeybees, and marine environments contain significant sequencing-adapter contamination that systematically reduces assembly accuracy and contiguousness. By removing the adapter-contaminated ends of contiguous sequences and reassembling MGnify reference genomes, we improve the quality of assemblies in these databases.

A genomic database furnishes minimal functional glycyl-tRNA synthetases homologous to other, designed class II urzymes.

The hypothesis that conserved core catalytic sites could represent ancestral aminoacyl-tRNA synthetases (AARS) drove the design of functional TrpRS, LeuRS, and HisRS 'urzymes'. We describe here new urzymes detected in the genomic record of the arctic fox, Vulpes lagopus. They are homologous to the α-subunit of bacterial heterotetrameric Class II glycyl-tRNA synthetase (GlyRS-B) enzymes. AlphaFold2 predicted that the N-terminal 81 amino acids would adopt a 3D structure nearly identical to our designed HisRS urzyme (HisCA1). We expressed and purified that N-terminal segment and the spliced open reading frame GlyCA1-2. Both exhibit robust single-turnover burst sizes and ATP consumption rates higher than those previously published for HisCA urzymes and comparable to those for LeuAC and TrpAC. GlyCA is more than twice as active in glycine activation by adenosine triphosphate as the full-length GlyRS-B α2 dimer. Michaelis-Menten rate constants for all three substrates reveal significant coupling between Exon2 and both substrates. GlyCA activation favors Class II amino acids that complement those favored by HisCA and LeuAC. Structural features help explain these results. These minimalist GlyRS catalysts are thus homologous to previously described urzymes. Their properties reinforce the notion that urzymes may have the requisite catalytic activities to implement a reduced, ancestral genetic coding alphabet.

CASRdb: A Publicly Accessible Comprehensive Database for Disease-associated Calcium-sensing Receptor Variants.

Genetic testing of the calcium-sensing receptor (CASR) gene is crucial for confirming diagnoses of familial hypocalciuric hypercalcemia type I (FHH1) and autosomal dominant hypocalcemia type I (ADH1). Therefore, we created a publicly accessible comprehensive database of the disease-causing variants of the CASR gene. We used two sources for variant reports: (1) we conducted a systematic review in the Embase and Pubmed databases from inception to March 2023, using search strategies associated with CASR. We identified all articles reporting CASR variants associated with disorders of calcium metabolism. (2) Additionally, data associated with pathogenic (P) or likely pathogenic (LP) variants in the ClinVar and LOVD databases were retrieved. Benign or likely benign variants were excluded. Variants of uncertain significance (VUS) were included only if they were reported in the literature. We generated a library of CASR variants associated with phenotypes, which has been made available on a website. We identified a total of 498 variants, of which 121 (24.3%) were associated with ADH1 and 377 (75.7%) with FHH1. Most included variants were identified from the literature (117 activating and 352 inactivating variants), and the majority of these were not documented in ClinVar/LOVD (73/117, 62.4% activating variants; 207/352, 58.8% inactivating variants). We developed CASRdb, a database that compiles information on all CASR variants associated with disorders of calcium metabolism from existing literature and genomic databases. Our database stands out due to the substantially higher number of disease-associated variants it contains, highlighting its comprehensive nature. The website is available at http://casrdb.mgh.harvard.edu.

Cation exchange resin coupled with bacterial pretreatment to promote waste activated sludge reduction: Performance and mechanism

Due to the rapid advancement of industrialization and urbanization, there has been a significant rise in the generation of industrial wastewater and domestic wastewater, which results in the rapid increase of waste activated sludge (WAS). However, the complex structure and slow hydrolysis of sludge limit aerobic digestion of WAS. This study evaluated the effect of lysozyme-secreting strain Proteus mirabilis sp. SJ25 and the new isolation of surfactant-secreting strain Enterobacter cloacae sp. WH11 on the promotion of sludge hydrolysis, and introduced cation exchange resin (CER) to enhance the promotion effect. The reduction efficiencies of suspended solids (SS) and volatile suspended solids (VSS) enhanced by 25.0 and 24.9 %, respectively, and the soluble chemical oxygen demand (SCOD) release was increased by 2370.27 mg/L when the inoculum of strain SJ25 and strain WH11 were 3 % and 6 %, and the dosage of CER was 2.0 g/g SS against the control. The fluorescence region integral (FRI) results showed a significant quantity of dissolved organic matter (DOM) was let out, and the biodegradability of the sludge was improved. The alterations in several physicochemical characteristics of the sludge also suggested that the extracellular polymeric substances (EPS) were disrupted and an enormous quantity of sludge cells were lysed. In addition, functional gene prediction from the Kyoto Encyclopedia of Genes and Genomes (KEGG) database indicated that CER coupled with bacterial pretreatment enhanced microbial metabolic capacity. This work suggests a novel pathway for the development of novel pretreatment methods to promote sludge hydrolysis.

Bacterial synergy and relay for thermophilic hydrogen production through dark fermentation using food waste

BackgroundFood waste is a significant global issue, with 1.3 billion tons generated annually, a figure expected to rise to 2.1 billion tons by 2030. Conventional disposal methods, such as landfilling and incineration, present environmental challenges, including methane emissions and pollution. Hydrogen production through dark fermentation presents a sustainable alternative, offering both waste management and renewable energy generation. This study investigates the bacterial synergy and relay mechanisms involved in thermophilic H2 production using food waste as a substrate. PurposeThe primary aim of this research was to analyze the metabolic pathways and dynamics of functional genes prediction during thermophilic H2 production from food waste, focusing on the role of bacterial consortia in enhancing H2 yields. MethodsA continuous stirred-tank reactor (CSTR) was operated using food waste as the substrate and a thermophilic bacterial consortium as the inoculum. The study utilized genomic analysis to monitor changes in bacteriobiome composition over time and to correlate these changes with H2 production. Volatile fatty acids (VFAs) and H2 production rates were analyzed using gas chromatography and high-performance liquid chromatography (HPLC). The Kyoto Encyclopedia of Genes and Genomes (KEGG) database was employed to identify functional genes involved in the fermentation process. ResultsThe study identified key bacterial species, including Caproiciproducens and Caproicibacter, that dominated during the later stages of H2 production, replacing earlier dominant species such as Clostridium. These shifts in bacterial dominance were strongly correlated with sustained H2 production rates ranging from 353 to 403 mL·L−1·h−1, with H2 concentrations between 55 % and 62 % (v/v). Functional gene analysis revealed significant pathways related to polysaccharide degradation, glycolysis, and dark fermentation. ConclusionsThis study highlights the importance of bacterial synergy and relay in maintaining continuous H2 production from food waste under thermophilic conditions. The findings provide insights into optimizing biohydrogen production processes, emphasizing the role of specific bacterial species in enhancing efficiency. These results contribute to the development of sustainable waste management strategies and renewable energy production.

The complete mitochondrial genome of Cylicocyclus ultrajectinus (Ihle, 1920)

In this study, the mitochondrial genome of Cylicocyclus ultrajectinus (Ihle, 1920) was sequenced for the first time using next-generation sequencing technology, and its compositional characteristics, structure, and phylogenetic relationship with other strongylid nematodes were analyzed by biological software. The results showed that these sequences contained 12 protein-coding genes, 22 tRNA genes, 2 rRNA genes, and 2 non-coding regions, all exhibiting a significant AT bias. Phylogenetic studies showed that C. ultrajectinus formed a distinct branch form other Cylicocyclus nematodes. This study contributes to the mitochondrial genome database of Strongylidae, laying a foundation for genetic variation, molecular classification, and evolutionary studies of strongylid nematodes.

Analysis of inactivating TSC1 and TSC2 alterations in a real-world patient population with advanced gynecologic cancers in the Foundation Medicine genomic database

Analysis of inactivating TSC1 and TSC2 alterations in a real-world patient population with advanced gynecologic cancers in the Foundation Medicine genomic database

Reference Sequence Browser: An R application with a user-friendly GUI to rapidly query sequence databases.

Land managers, researchers, and regulators increasingly utilize environmental DNA (eDNA) techniques to monitor species richness, presence, and absence. In order to properly develop a biological assay for eDNA metabarcoding or quantitative PCR, scientists must be able to find not only reference sequences (previously identified sequences in a genomics database) that match their target taxa but also reference sequences that match non-target taxa. Determining which taxa have publicly available sequences in a time-efficient and accurate manner currently requires computational skills to search, manipulate, and parse multiple unconnected DNA sequence databases. Our team iteratively designed a Graphic User Interface (GUI) Shiny application called the Reference Sequence Browser (RSB) that provides users efficient and intuitive access to multiple genetic databases regardless of computer programming expertise. The application returns the number of publicly accessible barcode markers per organism in the NCBI Nucleotide, BOLD, or CALeDNA CRUX Metabarcoding Reference Databases. Depending on the database, we offer various search filters such as min and max sequence length or country of origin. Users can then download the FASTA/GenBank files from the RSB web tool, view statistics about the data, and explore results to determine details about the availability or absence of reference sequences.