Recently, floating membrane filter cultivation was adopted to simulate solid surface and enrich surface-adapted soil ammonia-oxidizing archaea (AOA) communities from agricultural soil, as opposed to the conventional liquid medium. Here, we conducted metagenomic sequencing to recover nitrifier bins from the floating membrane filter cultures and reveal their genomic properties. Phylogenomic analysis showed that AOA bins recovered from this study, designated FF_bin01 and FF_bin02, are affiliated with the Nitrososphaeraceae family, while the third bin, FF_bin03, is a nitrite-oxidizing bacterium affiliated with the Nitrospiraceae family. Based on the ANI/AAI analysis, FF_bin01 and FF_bin02 are identified as novel species within the genera “Candidatus Nitrosocosmicus” and Nitrososphaera, respectively, while FF_bin03 represents a novel species within the genus Nitrospira. The pan and core genome analysis for the 29 AOA genomes considered in this study revealed 5,784 orthologous clusters, out of which 653 were core orthologous clusters. Additionally, 90 unique orthologous clusters were conserved among the Nitrososphaeraceae family, suggesting their potential role in enhancing culturability and adaptation to diverse environmental conditions. Intriguingly, FF_bin01 and FF_bin02 harbor a gene encoding manganese catalase and FF_bin03 also possesses a heme catalase gene, which might enhance their growth on the floating membrane filter. Overall, the floating membrane filter cultivation has proven to be a promising approach for isolating distinct soil AOA, and further modifications to this technique could stimulate the growth of a broader range of uncultivated nitrifiers from diverse soil environments.

Antimicrobial resistance (AMR) poses a serious threat to public health, with the emergence of extended-spectrum beta-lactamases (ESBLs) in Enterobacteriaceae, particularly Escherichia coli, raising significant concerns. This study aims to elucidate the drivers of antimicrobial resistance, and the global spread of cefotaxime-resistant E. coli (CREC) strains. Whole-genome sequencing (WGS) was performed to explore genome-level characteristics, and phylogenetic analysis was conducted to compare twenty CREC strains from this study, which were isolated from broiler chicken farms in Bangladesh, with a global collection (n = 456) of CREC strains from multiple countries and hosts. The MIC analysis showed over 70% of strains isolated from broiler chickens exhibiting MIC values ≥ 256 mg/L for cefotaxime. Notably, 85% of the studied farms (17/20) tested positive for CREC by the end of the production cycle, with CREC counts increasing from 0.83 ± 1.75 log10 CFU/g feces on day 1 to 5.24 ± 0.72 log10 CFU/g feces by day 28. WGS revealed the presence of multiple resistance genes, including bla_CTX-M, which was found in 30% of the strains. Phylogenetic comparison showed that the Bangladeshi strains were closely related to strains from diverse geographical regions and host species. This study provides a comprehensive understanding of the molecular epidemiology of CREC. The close phylogenetic relationships between Bangladeshi and global strains demonstrate the widespread presence of cefotaxime-resistant bacteria and emphasize the importance of monitoring AMR in food-producing animals to mitigate the spread of resistant strains.

Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) technologies have emerged as powerful tools for precise genome editing, leading to a revolution in genetic research and biotechnology across diverse organisms including microalgae. Since the 1950s, microalgal production has evolved from initial cultivation under controlled conditions to advanced metabolic engineering to meet industrial demands. However, effective genetic modification in microalgae has faced significant challenges, including issues with transformation efficiency, limited target selection, and genetic differences between species, as interspecies genetic variation limits the use of genetic tools from one species to another. This review summarized recent advancements in CRISPR systems applied to microalgae, with a focus on improving gene editing precision and efficiency, while addressing organism-specific challenges. We also discuss notable successes in utilizing the class 2 CRISPR-associated (Cas) proteins, including Cas9 and Cas12a, as well as emerging CRISPR-based approaches tailored to overcome microalgal cellular barriers. Additionally, we propose future perspectives for utilizing CRISPR/Cas strategies in microalgal biotechnology.

Existing microbial engineering strategies—encompassing metabolic engineering, systems biology, and systems metabolic engineering—have significantly enhanced the potential of microbial cell factories as sustainable alternatives to the petrochemical industry by optimizing metabolic pathways. Recently, systems metabolic engineering, which integrates tools from synthetic biology, enzyme engineering, omics technology, and evolutionary engineering, has been successfully developed. By leveraging modern engineering strategies within the Design-Build-Test-Learn (DBTL) cycle framework, these advancements have revolutionized the biosynthesis of valuable compounds. This review highlights recent progress in the metabolic engineering of Corynebacterium glutamicum, a versatile microbial platform, achieved through various approaches from traditional metabolic engineering to advanced systems metabolic engineering, all within the DBTL cycle. A particular focus is placed C5 platform chemicals derived from L-lysine, one of the key amino acid production pathways of C. glutamicum. The development of DBTL cycle-based metabolic engineering strategies for this process is discussed.

Microbial biosynthesis using yeast species offers numerous advantages to produce industrially relevant biofuels and biochemicals. Conventional metabolic engineering approaches in yeast focus on biosynthetic pathways in the cytoplasm, but these approaches are disturbed by various undesired factors including metabolic crosstalk, competing pathways and insufficient precursors. Given that eukaryotic cells contain subcellular organelles with distinct physicochemical properties, an emerging strategy to overcome cytosolic pathway engineering bottlenecks is through repurposing these organelles as specialized microbial cell factories for enhanced production of valuable chemicals. Here, we review recent progress and significant outcomes of harnessing organelle engineering for biofuels and biochemicals production in both conventional and non-conventional yeasts. We highlight key engineering strategies for the compartmentalization of biosynthetic pathways within specific organelles such as mitochondria, peroxisomes, and endoplasmic reticulum; involved in engineering of signal peptide, cofactor and energy enhancement, organelle biogenesis and dual subcellular engineering. Finally, we discuss the potential and challenges of organelle engineering for future studies and propose an automated pipeline to fully exploit this approach.

Bacteria-free reverse genetics techniques are crucial for the efficient generation of recombinant viruses, bypassing the need for labor-intensive bacterial cloning. These methods are particularly relevant for studying the pathogenesis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of COVID-19. This study compared the efficiency of three bacteria-free approaches—circular polymerase extension reaction (CPER) with and without nick sealing and infectious sub-genomic amplicons (ISA)—to bacterial artificial chromosome (BAC)-based technology for rescuing SARS-CoV-2. Significant differences in viral titers following transfection were observed between methods. CPER with nick sealing generated virus titers comparable to those of the BAC-based method and 10 times higher than those of the standard CPER. In contrast, ISA demonstrated extremely low efficiency, as cytopathic effects were detected only after two passages. All rescued viruses exhibited replication kinetics consistent with those of the original strain, with no significant deviation in replication capacity. Furthermore, the utility of CPER and ISA in genetically modifying SARS-CoV-2 was demonstrated by successfully inserting the gene encoding green fluorescent protein into the genome. Overall, this study underscores the potential of bacteria-free methods, such as CPER and ISA, in advancing SARS-CoV-2 research while highlighting their significant differences in efficiency.

Synbiotics have become a new-age treatment tool for limiting the progression of metabolic dysfunction-associated steatotic liver disease; however, inclusive comparisons of various synbiotic treatments are still lacking. Here, we have explored and evaluated multiple synbiotic combinations incorporating three distinctive prebiotics, lactitol, lactulose and fructooligosaccharides. Of the synbiotic treatments evaluated, a combination of fructooligosaccharides and probiotics (FOS+Pro) exhibited superior protection against western diet-induced liver degeneration. This synbiotic (FOS+Pro) combination resulted in the lowest body weight gains, liver weights and liver/body weight ratios. The FOS+Pro synbiotic combination substantially alleviated liver histopathological markers and reduced serum AST and cholesterol levels. FOS+Pro ameliorated hepatic inflammation by lowering expression of proinflammatory markers including TNF-α, IL-1β, IL-6, and CCL2. FOS+Pro significantly improved steatosis by restricting the expression of lipid metabolic regulators (ACC1, FAS) and lipid transporters (CD36) in the liver. These findings are critical in suggesting that synbiotic treatments are capable of restraining western diet-induced metabolic dysfunction in the liver. Additionally, this study demonstrated that adding probiotic strains amplified the effectiveness of fructooligosaccharides but not all prebiotics.

This review explores current advancements in microbiome functional analysis enabled by next-generation sequencing technologies, which have transformed our understanding of microbial communities from mere taxonomic composition to their functional potential. We examine approaches that move beyond species identification to characterize microbial activities, interactions, and their roles in host health and disease. Genome-scale metabolic models allow for in-depth simulations of metabolic networks, enabling researchers to predict microbial metabolism, growth, and interspecies interactions in diverse environments. Additionally, computational methods for predicting metabolite profiles offer indirect insights into microbial metabolic outputs, which is crucial for identifying biomarkers and potential therapeutic targets. Functional pathway analysis tools further reveal microbial contributions to metabolic pathways, highlighting alterations in response to environmental changes and disease states. Together, these methods offer a powerful framework for understanding the complex metabolic interactions within microbial communities and their impact on host physiology. While significant progress has been made, challenges remain in the accuracy of predictive models and the completeness of reference databases, which limit the applicability of these methods in under-characterized ecosystems. The integration of these computational tools with multi-omic data holds promise for personalized approaches in precision medicine, allowing for targeted interventions that modulate the microbiome to improve health outcomes. This review highlights recent advances in microbiome functional analysis, providing a roadmap for future research and translational applications in human health and environmental microbiology.

With the advent of whole-genome sequencing, opportunities to investigate the population structure, transmission patterns, antimicrobial resistance profiles, and virulence determinants of Streptococcus pneumoniae at high resolution have been increasingly expanding. Consequently, a user-friendly bioinformatics tool is needed to automate the analysis of Streptococcus pneumoniae whole-genome sequencing data, summarize clinically relevant genomic features, and further guide treatment options. Here, we developed PneusPage, a web-based tool that integrates functions for species prediction, molecular typing, drug resistance determination, and data visualization of Streptococcus pneumoniae. To evaluate the performance of PneusPage, we analyzed 80 pneumococcal genomes with different serotypes from the Global Pneumococcal Sequencing Project and compared the results with those from another platform, PathogenWatch. We observed a high concordance between the two platforms in terms of serotypes (100% concordance rate), multilocus sequence typing (100% concordance rate), penicillin-binding protein typing (88.8% concordance rate), and the Global Pneumococcal Sequencing Clusters (98.8% concordance rate). In addition, PneusPage offers integrated analysis functions for the detection of virulence and mobile genetic elements that are not provided by previous platforms. By automating the analysis pipeline, PneusPage makes whole-genome sequencing data more accessible to non-specialist users, including microbiologists, epidemiologists, and clinicians, thereby enhancing the utility of whole-genome sequencing in both research and clinical settings. PneusPage is available at https://pneuspage.minholee.net/.

Systemic sclerosis (SSc) is a chronic autoimmune disorder characterised by skin fibrosis and internal organ involvement. Disruptions in the microbial communities on the skin may contribute to the onset of autoimmune diseases that affect the skin. However, current research on the skin microbiome in SSc is lacking. This study aimed to investigate skin microbiome associated with disease severity in SSc. Skin swabs were collected from the upper limbs of 46 healthy controls (HCs) and 36 patients with SSc. Metagenomic analysis based on the 16S rRNA gene was conducted and stratified by cutaneous subtype and modified Rodnan skin score (mRSS) severity. Significant differences in skin bacterial communities were observed between the HCs and patients with SSc, with further significant variations based on subtype and mRSS severity. The identified biomarkers were Bacteroides and Faecalibacterium for patients with diffuse cutaneous SSc with high mRSS (≥ 10) and Mycobacterium and Parabacteroides for those with low mRSS (< 10). Gardnerella, Abies, Lactobacillus, and Roseburia were the biomarkers in patients with limited cutaneous SSc (lcSS) and high mRSS, whereas Coprococcus predominated in patients with lcSS and low mRSS. Cutaneous subtype analysis identified Pediococcus as a biomarker in the HCs, whereas mRSS analysis revealed the presence of Pseudomonas in conjunction with Pediococcus. In conclusion, patients with SSc exhibit distinct skin microbiota compared with healthy controls. Bacterial composition varies by systemic sclerosis cutaneous subtype and skin thickness.