MultiPrime: A reliable and efficient tool for targeted next-generation sequencing

Integrated analysis of microbiome and metabolome reveals insights into cervical neoplasia aggravation in a Chinese cohort

Introduction

Cervical carcinoma (CC) remains one of the significant cancers threatening women's health globally. Increasing evidence suggests that alterations in the microbiota are closely associated with cancer development. However, the understanding of reliable biomarkers and underlying mechanisms during the aggravation of cervical neoplasia such as cervical intraepithelial neoplasia (CIN) and CC is still relatively limited.

Methods

In this study, cervical swab samples from 53 healthy controls, 51 high-grade squamous intraepithelial lesion (HSIL), and 52 CC patients were subjected to 16S rDNA sequencing and metabolomics analysis.

Results

We observed significant differences in the cervical microbiota between CC patients and healthy controls or HSIL groups. Compared to the healthy controls, CC patients exhibited increased microbial diversity, decreased abundance of Lactobacillus, and notable changes in microbial composition. Metabolomics analysis revealed significantly elevated levels of the inflammatory mediator Prostaglandin E2 (PGE2) in CC samples. Through random forest modeling and ROC curve analysis, we identified a combination of key microbiota (Porphyromonas, Pseudofulvibacter) and metabolites (Cellopentaose, PGE2) as diagnostic biomarkers with high diagnostic value for CC. Furthermore, we found a significant correlation between the cervical microbiota Porphyromonas and the metabolite PGE2, suggesting a potential role of key microbiota in inducing inflammation.

Discussion

These findings indicate that alterations in cervical microbiota and metabolites may be closely associated with the occurrence and aggravation of cervical neoplasia, providing new insights for further understanding the mechanisms of cervical neoplasia progression and developing novel diagnostic markers and therapeutic approaches.

Rapidly obtaining genome sequence of Severe Fever with Thrombocytopenia Syndrome virus directly from clinical serum specimen using long amplicon based nanopore sequencing workflow

Severe Fever with Thrombocytopenia Syndrome (SFTS) is an emerging viral infectious disease discovered in 2009 with a high fatality rate and continuing to pose a public threat for many countries. Surveillance of genome sequence of its causative pathogen, Severe Fever with Thrombocytopenia Syndrome virus (SFTSV), could provide evidence for SFTS control, diagnosis method update, viral evolution dynamic and pathogenic mechanism research, etc. Here, we developed a workflow for rapidly obtaining the genome sequence of SFTSV directly from clinical samples to facilitate the viral genome sequence surveillance. Three pairs of primers targeting the terminal conserved regions of three segments were newly designed to more efficiently enrich nearly whole viral genome. Datasets comprised reads generated in different timeframes for four simulated samples with high to low serially diluted viral loads were subjected to analysis. For a simulated sample with a Ct value of 35 and sequenced for 10 minutes, the average coverage depth could reach over 700x, and the genome coverage could reach 98.69% after subtraction of the primer sequence, and the sequence identity with Sanger sequencing could reach over 99.91%. Two clinical serum specimens were used to validate the workflow and sequences were successfully obtained. A long amplicon based nanopore sequencing workflow was established, which could finish in 10 hours from serum specimen to genome sequence. This workflow has potential to provide essential information for SFTS control and support further pathogenesis research.

A chromosome-level genome assembly and annotation of the Pseudorasbora elongata (Cypriniformes: Cyprinidae)

Pseudorasbora elongata is a unique small fish species endemic to China, distinguished by its striking body coloration resembling a "Chinese ink brush." Due to environmental changes and anthropogenic factors, its wild populations have declined, and it has been listed multiple times as an endangered species. However, the absence of a chromosomal-level reference for P. elongata has hindered our understanding of its population genetics and conservation biology. To address this gap, we present a chromosome-level genome assembly of P. elongata, generated using PacBio HiFi reads, Oxford Nanopore Technologies, and Hi-C data. We get a genome size of 1.4 Gb with a contig N50 of 34.4 Mb and a scafold N50 of 53.7 Mb. Telomeric sequences were identified at the ends of 42 telomeres across 25 chromosomes. Notably, we observed a high degree of collinearity between our assembly and the Pseudorasbora parva genome. This study provides valuable insights into the genetics, genomics, and evolutionary history of P. elongata, offering a foundation for future research and enabling the development of genetic conservation strategies.

Enhancing Arthropod Diversity and Sorghum Quality in Northern Jiangsu, China: The Benefits of Green Pest Management Revealed Through Metabarcoding

Sorghum is a key global crop with substantial economic importance. Implementing green pest management for sorghum is crucial for promoting ecological balance and reducing reliance on chemical pesticides. This study assesses the impact of green pest management on arthropod biodiversity and sorghum yield and quality. Over two years, using Malaise trapping and DNA metabarcoding, we found that green pest management significantly enhanced arthropod diversity, increasing species richness by 5.63% and shifting species composition, notably increasing the abundance of Hymenoptera. Although sorghum yield metrics were higher in the green group compared to the chemical control group, these differences were not statistically significant. However, the green group exhibited improved quality with lower crude fat (3.63% vs. 4.08% in the chemical control group) and higher levels of crude protein (9.18% vs. 9.13%), starch (73.69% vs. 73.41%), and amylopectin (98.53% vs. 98.34%). These findings underscore the benefits of green pest management in fostering biodiversity and enhancing sorghum quality. Future research should focus on optimizing biodiversity-driven agroecosystem resilience and scaling these strategies across diverse agricultural systems.

Enhancing bloodstream infection diagnostics: a novel filtration and targeted next-generation sequencing approach for precise pathogen identification

Bloodstream infections (BSIs) pose a significant diagnostic challenge, largely due to the limitations of traditional methods such as blood cultures. These methods often yield low positive rates, have lengthy processing times that delay treatment, and are limited in detecting only a narrow range of pathogens. Such delays and inaccuracies can critically impede timely clinical interventions, potentially compromising patient outcomes. Next-generation sequencing (NGS) is a powerful tool for rapid, precise pathogen identification. While metagenomic NGS (mNGS) offers broad pathogen coverage, it is often costly and complex. Targeted NGS (tNGS), however, focuses on key regions of clinically relevant pathogens, reducing costs and simplifying workflows while maintaining high sensitivity, making it more practical for routine diagnostics. In this study, we introduce a novel approach combining a human cell-specific filtration membrane with a multiplex tNGS panel to overcome these challenges. The filtration membrane, designed with surface charge properties to be electrostatically attractive to leukocytes for the selective capture of specific cells, demonstrated high efficiency in removing host cells and nucleic acids, achieving over a 98% reduction in host DNA and thereby minimizing background interference in pathogen detection. Additionally, we developed an effective multiplex tNGS panel targeting over 330 clinically relevant pathogens and verified its consistency with mNGS and blood culture results, demonstrating a significant improvement in detection sensitivity. By integrating these two methods, we achieved a synergistic enhancement in diagnostic capability, boosting pathogen reads by 6- to 8-fold, which enabled reliable identification even in cases of low-abundance pathogens. This approach provides faster, more accurate, and more sensitive detection of BSIs, enabling earlier identification of infections. This facilitates timely and targeted treatment, ultimately improving patient outcomes in critical care settings. Given the unique properties of the filtration membrane and the strengths of the tNGS panel, this approach shows promising applications in prenatal and genetic health support, as well as in advancing early cancer screening strategies.

Metabolomic and Transcriptomic Analyses of Flavonoid Biosynthesis in Dendrobium devonianum Flowers

BACKGROUND

Dendrobium devonianum is a traditional Chinese medicinal herb with notable ornamental and medicinal value.

METHODS

In this study, transcriptomic and metabolomic approaches were employed to investigate gene expression and secondary metabolite changes during four developmental stages of D. devonianum flowers.

RESULTS

Metabolomic analysis identified 1186 distinct metabolites, with flavonoid compounds being the most abundant category (213 types). Transcriptomic analysis revealed 31 differentially expressed genes associated with flavonoid biosynthesis and flavonoid and flavonol biosynthesis pathways. Among these, key genes regulating flavonol synthesis, including F3H (Unigene0077194) and FLS (Unigene0062137), exhibited high expression levels in the early developmental stage (S1).

CONCLUSIONS

Flavonoids serve as the major active components in D. devonianum flowers, exhibiting a wide range of pharmacological properties. This study provides valuable insights into the molecular mechanisms driving flavonoid accumulation in D. devonianum, offering a foundation for further functional studies and applications in ornamental and medicinal plant research.

Clinical application of targeted next-generation sequencing in pneumonia diagnosis among cancer patients

Background

Cancer patients are highly susceptible to infections due to their immunocompromised state from both the malignancy and intensive treatments. Accurate and timely identification of causative pathogens is crucial for effective management and treatment. Targeted next-generation sequencing (tNGS) has become an important tool in clinical infectious disease diagnosis because of its broad microbial detection range and acceptable cost. However, there is currently a lack of systematic research to evaluate the diagnostic value of this method in cancer patients.

Methods

To evaluate the diagnostic value of tNGS for cancer patients with pneumonia, a retrospective analysis was conducted on 148 patients with suspected pneumonia who were treated at the Henan Cancer Hospital. The tNGS results were compared with conventional microbiological tests (CMT) and clinical diagnoses based on symptoms and imaging studies to assess the diagnostic performance of tNGS in cancer patients with pneumonia.

Results

Among these 148 patients, 130 were ultimately diagnosed with pneumonia. tNGS demonstrated significantly higher sensitivity (84.62% vs. 56.92%) and diagnostic accuracy (85.81% vs. 62.16%) compared to the CMT method. The tNGS method identified more pathogens than CMT method (87.50% vs 57.14%), regardless of whether they were bacteria, fungi, or viruses, primarily due to its broader pathogen detection range and higher sensitivity compared to the CMT method. tNGS had significantly higher diagnostic accuracy for Pneumocystis jirovecii and Legionella pneumophila than the CMT method, but for most pathogens, tNGS showed higher sensitivity but with a correspondingly lower specificity compared to CMT.

Conclusion

tNGS demonstrates higher sensitivity and a broader pathogen detection spectrum compared to CMT, making it a valuable diagnostic tool for managing pneumonia in cancer patients.

Clinical diagnosis of Q fever by targeted next-generation sequencing for identification of Coxiella burnetii

PURPOSE

Q fever is a zoonotic bacterial disease caused by Coxiella burnetii. Due to its variable and non-specific clinical symptoms, the disease is often overlooked and underreported. To date, the identification of C. burnetii as the causative pathogen of Q fever using targeted next-generation sequencing (tNGS) has not been previously documented.

METHODS

tNGS was performed on patients with acute fever of unknown etiology, and qPCR was confirmed for C. burnetii infection.

RESULTS

tNGS was performed on 112 patients with acute fever of unknown etiology at Peking University Third Hospital between March 27 and September 20, 2024. C. burnetii was identified in blood samples from five patients, leading to a clinical diagnosis of Q fever. These diagnoses were subsequently confirmed by qPCR at the Beijing CDC. The mean age of the patients was 39.6 years (range: 32-59 years). Although blood cultures were negative, elevated infection markers (CRP, PCT, and ferritin) and liver enzymes (ALT, AST, GGT, ALP, and LDH) were observed. No epidemiological links to Q fever were identified in these cases. All five patients were treated promptly with oral doxycycline (0.1 g twice daily for 2 weeks) and discharged in improved health.

CONCLUSIONS

tNGS is a promising and significant tool for rapidly detecting C. burnetii infection.

MicrobiomeStatPlots: Microbiome statistics plotting gallery for meta-omics and bioinformatics

The rapid growth of microbiome research has generated an unprecedented amount of multi-omics data, presenting challenges in data analysis and visualization. To address these issues, we present MicrobiomeStatPlots, a comprehensive platform offering streamlined, reproducible tools for microbiome data analysis and visualization. This platform integrates essential bioinformatics workflows with multi-omics pipelines and provides 82 distinct visualization cases for interpreting microbiome datasets. By incorporating basic tutorials and advanced R-based visualization strategies, MicrobiomeStatPlots enhances accessibility and usability for researchers. Users can customize plots, contribute to the platform's expansion, and access a wealth of bioinformatics knowledge freely on GitHub (https://github.com/YongxinLiu/MicrobiomeStatPlot). Future plans include extending support for metabolomics, viromics, and metatranscriptomics, along with seamless integration of visualization tools into omics workflows. MicrobiomeStatPlots bridges gaps in microbiome data analysis and visualization, paving the way for more efficient, impactful microbiome research.

EasyMetagenome: A user-friendly and flexible pipeline for shotgun metagenomic analysis in microbiome research

Shotgun metagenomics has become a pivotal technology in microbiome research, enabling in-depth analysis of microbial communities at both the high-resolution taxonomic and functional levels. This approach provides valuable insights of microbial diversity, interactions, and their roles in health and disease. However, the complexity of data processing and the need for reproducibility pose significant challenges to researchers. To address these challenges, we developed EasyMetagenome, a user-friendly pipeline that supports multiple analysis methods, including quality control and host removal, read-based, assembly-based, and binning, along with advanced genome analysis. The pipeline also features customizable settings, comprehensive data visualizations, and detailed parameter explanations, ensuring its adaptability across a wide range of data scenarios. Looking forward, we aim to refine the pipeline by addressing host contamination issues, optimizing workflows for third-generation sequencing data, and integrating emerging technologies like deep learning and network analysis, to further enhance microbiome insights and data accuracy. EasyMetageonome is freely available at https://github.com/YongxinLiu/EasyMetagenome.

Advances and challenges in molecular understanding, early detection, and targeted treatment of liver cancer

In this review, we explore the application of next-generation sequencing in liver cancer research, highlighting its potential in modern oncology. Liver cancer, particularly hepatocellular carcinoma, is driven by a complex interplay of genetic, epigenetic, and environmental factors. Key genetic alterations, such as mutations in TERT, TP53, and CTNNB1, alongside epigenetic modifications such as DNA methylation and histone remodeling, disrupt regulatory pathways and promote tumorigenesis. Environmental factors, including viral infections, alcohol consumption, and metabolic disorders such as nonalcoholic fatty liver disease, enhance hepatocarcinogenesis. The tumor microenvironment plays a pivotal role in liver cancer progression and therapy resistance, with immune cell infiltration, fibrosis, and angiogenesis supporting cancer cell survival. Advances in immune checkpoint inhibitors and chimeric antigen receptor T-cell therapies have shown potential, but the unique immunosuppressive milieu in liver cancer presents challenges. Dysregulation in pathways such as Wnt/β-catenin underscores the need for targeted therapeutic strategies. Next-generation sequencing is accelerating the identification of genetic and epigenetic alterations, enabling more precise diagnosis and personalized treatment plans. A deeper understanding of these molecular mechanisms is essential for advancing early detection and developing effective therapies against liver cancer.

A Chromosomal-level genome assembly and annotation of fat greenling (Hexagrammos otakii)

Fat greenling (Hexagrammos otakii Jordan & Starks, 1895) is a valuable marine fish species, crucial for aquaculture in Northern China due to its high-quality meat and significant economic value. However, the aquaculture industry faces challenges such as trait degradation, early sexual maturity, and disease susceptibility, necessitating advanced genomic interventions for sustainable cultivation. This study presents the first chromosomal-level genome assembly of H. otakii, achieved using PacBio long-read sequencing and Hi-C technology. The assembly yielded a genome size of 682.43 Mb with a contig N50 size of 2.39 Mb and a scaffold N50 size of 27.83 Mb. The completeness of genome assessed by BUSCO is 96.99%. A total of 22,334 protein-coding genes were predicted, with 21,619 (96.80%) functionally annotated across various protein databases. This genomic resource is a step forward in supporting the breeding, germplasm conservation, and enhancement of H. otakii, facilitating genetic studies and the development of strategies for disease resistance and growth optimization in aquaculture.

Benchmarking short-read metagenomics tools for removing host contamination

BACKGROUND

The rapid evolution of metagenomic sequencing technology offers remarkable opportunities to explore the intricate roles of microbiome in host health and disease, as well as to uncover the unknown structure and functions of microbial communities. However, the swift accumulation of metagenomic data poses substantial challenges for data analysis. Contamination from host DNA can substantially compromise result accuracy and increase additional computational resources by including nontarget sequences.

RESULTS

In this study, we assessed the impact of computational host DNA decontamination on downstream analyses, highlighting its importance in producing accurate results efficiently. We also evaluated the performance of conventional tools like KneadData, Bowtie2, BWA, KMCP, Kraken2, and KrakenUniq, each offering unique advantages for different applications. Furthermore, we highlighted the importance of an accurate host reference genome, noting that its absence negatively affected the decontamination performance across all tools.

CONCLUSIONS

Our findings underscore the need for careful selection of decontamination tools and reference genomes to enhance the accuracy of metagenomic analyses. These insights provide valuable guidance for improving the reliability and reproducibility of microbiome research.

Rapid quantitative PCR on tongue swabs for pulmonary tuberculosis in adults: a prospective multicentre study

BACKGROUND

Tuberculosis (TB) remains a major cause of infectious disease mortality globally, with significant underdiagnosis perpetuating transmission. Tongue swab analysis has emerged as a promising non-invasive method for pulmonary TB diagnosis. This study evaluates the diagnostic accuracy of the TB-EASY quantitative PCR (qPCR) assay using tongue swab specimens.

METHODS

In this prospective multicentre study, conducted across seven designated TB hospitals in China, 729 participants were included in the analysis. Tongue swabs were tested using the new TB-EASY assay from Hugobiotech, while sputum samples were analysed by Xpert MTB/RIF (Xpert), smear and culture tests. Diagnostic performance was compared to a composite microbiological reference standard (MRS).

RESULTS

The TB-EASY assay demonstrated high diagnostic accuracy, with sensitivity and specificity of 89.6% and 96.2% compared to sputum Xpert, and 87.4% and 98.0% compared to the MRS. Sensitivity varied by bacterial load, ranging from 100% in high-load cases to 70.4% in very-low-load cases. The assay demonstrated robust performance in diverse epidemiological settings.

CONCLUSIONS

The TB-EASY qPCR assay using tongue swabs offers a reliable, non-invasive diagnostic alternative for pulmonary TB, especially where sputum collection is challenging. Its potential for wider use in high TB burden settings warrants further validation in community-based studies. Limitations include potential overestimation of sensitivity due to the selection of symptomatic patients and the use of sputum Xpert rather than Xpert Ultra. Additionally, the performance in non-sputum-producing patients remains untested, and the cost-effectiveness should be further evaluated to assess the feasibility of its implementation.

Integrated transcriptomic, proteomic and metabolomic analyses revealing the roles of amino acid and sucrose metabolism in augmenting drought tolerance in Agropyron mongolicum

Drought, a major consequence of climate change, initiates molecular interactions among genes, proteins, and metabolites. Agropyron mongolicum a high-quality perennial grass species, exhibits robust drought resistance. However, the molecular mechanism underlying this resistance remaining largely unexplored. In this study, we performed an integrated analysis of the transcriptome, proteome, and metabolome of A. mongolicum under optimal and drought stress conditions. This combined analysis highlighted the pivotal role of transporters in responding to drought stress. Moreover, metabolite profiling indicated that arginine and proline metabolism, as well as the pentose phosphate pathway, are significantly involved in the drought response of A. mongolicum. Additionally, the integrated analysis suggested that proline metabolism and the pentose phosphate pathway are key elements of the drought resistance strategy in A. mongolicum plants. In summary, our research elucidates the drought adaptation mechanisms of A. mongolicum and identifies potential candidate genes for further study.

Genetic variation features of neonatal hyperbilirubinemia caused by inherited diseases

BACKGROUND

Genetic factors play an important role in neonatal hyperbilirubinemia (NH) caused by genetic diseases.

AIM

To explore the characteristics of genetic mutations associated with NH and analyze the correlation with genetic diseases.

METHODS

This was a retrospective cohort study. One hundred and five newborn patients diagnosed with NH caused by genetic diseases were enrolled in this study between September 2020 and June 2023 at the Second Affiliated Hospital of Xiamen Medical College. A 24-gene panel was used for gene sequencing to analyze gene mutations in patients. The data were analyzed via Statistical Package for the Social Sciences 20.0 software.

RESULTS

Seventeen frequently mutated genes were found in the 105 patients. Uridine 5'-diphospho-glucuronosyltransferase 1A1 (UGT1A1) variants were identified among the 68 cases of neonatal Gilbert syndrome. In patients with sodium taurocholate cotransporting polypeptide deficiency, the primary mutation identified was Na+/taurocholate cotransporting polypeptide Ntcp (SLC10A1). Adenosine triphosphatase 7B (ATP7B) mutations primarily occur in patients with hepatolenticular degeneration (Wilson's disease). In addition, we found that UGT1A1 and glucose-6-phosphate dehydrogenase mutations were more common in the high-risk group than in the low-risk group, whereas mutations in SLC10A1, ATP7B, and heterozygous 851del4 mutation were more common in the low-risk group.

CONCLUSION

Genetic mutations are associated with NH and significantly increase the risk of disease in affected newborns.

Transcription-Associated Metabolomic Analysis Reveals the Mechanism of Fruit Ripening during the Development of Chinese Bayberry

The ripening process of Chinese bayberries (Myrica rubra) is intricate, involving a multitude of molecular interactions. Here, we integrated transcriptomic and metabolomic analysis across three developmental stages of the Myrica rubra (M. rubra) to elucidate these processes. A differential gene expression analysis categorized the genes into four distinct groups based on their expression patterns. Gene ontology and pathway analyses highlighted processes such as cellular and metabolic processes, including protein and sucrose metabolism. A metabolomic analysis revealed significant variations in metabolite profiles, underscoring the dynamic interplay between genes and metabolites during ripening. Flavonoid biosynthesis and starch and sucrose metabolism were identified as key pathways, with specific genes and metabolites playing crucial roles. Our findings provide insights into the molecular mechanisms governing fruit ripening in M. rubra and offer potential targets for breeding strategies aimed at enhancing fruit quality.

Application of metagenomic next-generation sequencing and targeted metagenomic next-generation sequencing in diagnosing pulmonary infections in immunocompetent and immunocompromised patients

Background

Metagenomic next-generation sequencing (mNGS) technology has been widely used to diagnose various infections. Based on the most common pathogen profiles, targeted mNGS (tNGS) using multiplex PCR has been developed to detect pathogens with predesigned primers in the panel, significantly improving sensitivity and reducing economic burden on patients. However, there are few studies on summarizing pathogen profiles of pulmonary infections in immunocompetent and immunocompromised patients in Jilin Province of China on large scale.

Methods

From January 2021 to December 2023, bronchoalveolar lavage fluid (BALF) or sputum samples from 546 immunocompetent and immunocompromised patients with suspected community-acquired pneumonia were collected. Pathogen profiles in those patients on whom mNGS was performed were summarized. Additionally, we also evaluated the performance of tNGS in diagnosing pulmonary infections.

Results

Combined with results of mNGS and culture, we found that the most common bacterial pathogens were Pseudomonas aeruginosa, Klebsiella pneumoniae, and Acinetobacter baumannii in both immunocompromised and immunocompetent patients with high detection rates of Staphylococcus aureus and Enterococcus faecium, respectively. For fungal pathogens, Pneumocystis jirovecii was commonly detected in patients, while fungal infections in immunocompetent patients were mainly caused by Candida albicans. Most of viral infections in patients were caused by Human betaherpesvirus 5 and Human gammaherpesvirus 4. It is worth noting that, compared with immunocompetent patients (34.9%, 76/218), more mixed infections were found in immunocompromised patients (37.8%, 14/37). Additionally, taking final comprehensive clinical diagnoses as reference standard, total coincidence rate of BALF tNGS (81.4%, 48/59) was much higher than that of BALF mNGS (40.0%, 112/280).

Conclusions

Our findings supplemented and classified the pathogen profiles of pulmonary infections in immunocompetent and immunocompromised patients in Jilin Province of China. Most importantly, our findings can accelerate the development and design of tNGS specifically used for regional pulmonary infections.

Genome-wide association studies reveal novel QTLs for agronomic traits in soybean

Introduction

Soybean, as a globally significant crop, has garnered substantial attention due to its agricultural importance. The utilization of molecular approaches to enhance grain yield in soybean has gained popularity.

Methods

In this study, we conducted a genome-wide association study (GWAS) using 156 Chinese soybean accessions over a two-year period. We employed the general linear model (GLM) and the mixed linear model (MLM) to analyze three agronomic traits: pod number, grain number, and grain weight.

Results

Our findings revealed significant associations between qgPNpP-98, qgGNpP-89 and qgHGW-85 QTLs and pod number, grain number, and grain weight, respectively. These QTLs were identified on chromosome 16, a region spanning 413171bp exhibited associations with all three traits.

Discussion

These QTL markers identified in this study hold potential for improving yield and agronomic traits through marker-assisted selection and genomic selection in breeding programs.

Genome-scale cis-acting catabolite-responsive element editing confers Bacillus pumilus LG3145 plant-beneficial functions

Rhizosphere dwelling microorganism such as Bacillus spp. are helpful for crop growth. However, these functions are adversely affected by long-term synthetic fertilizer application. We developed a modified CRISPR/Cas9 system using non-specific single-guide RNAs to disrupt the genome-wide cis-acting catabolite-responsive elements (cres) in a wild-type Bacillus pumilus strain, which conferred dual plant-benefit properties. Most of the mutations occurred around imperfectly matched cis-acting elements (cre-like sites) in genes that are mainly involved in carbon and secondary metabolism pathways. The comparative metabolomics and transcriptome results revealed that carbon is likely transferred to some pigments, such as riboflavin, carotenoid, and lycopene, or non-ribosomal peptides, such as siderophore, surfactin, myxochelin, and bacilysin, through the pentose phosphate and amino acid metabolism pathways. Collectively, these findings suggested that the mutation of global cre-like sequences in the genome might alter carbon flow, thereby allowing beneficial biological interactions between the rhizobacteria and plants.

Wekemo Bioincloud: A user-friendly platform for meta-omics data analyses

The increasing application of meta-omics approaches to investigate the structure, function, and intercellular interactions of microbial communities has led to a surge in available data. However, this abundance of human and environmental microbiome data has exposed new scalability challenges for existing bioinformatics tools. In response, we introduce Wekemo Bioincloud-a specialized platform for -omics studies. This platform offers a comprehensive analysis solution, specifically designed to alleviate the challenges of tool selection for users in the face of expanding data sets. As of now, Wekemo Bioincloud has been regularly equipped with 22 workflows and 65 visualization tools, establishing itself as a user-friendly and widely embraced platform for studying diverse data sets. Additionally, the platform enables the online modification of vector outputs, and the registration-independent personalized dashboard system ensures privacy and traceability. Wekemo Bioincloud is freely available at https://www.bioincloud.tech/.