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Klebsiella pneumoniae is a Gram-negative opportunistic pathogenic bacterium that occasionally inhabits the human gastrointestinal tracts. Gut-colonized K. pneumoniae may then metastasize to other organs and tissues, thus causing severe infections. In this study, we identified three cpxA mutations in K. pneumoniae that experimentally evolved to show reduced adhesive ability. CpxA is a sensor histidine kinase that rendered reduced surface adhesion and gut colonization ability in K. pneumoniae. Interestingly, one experimentally gained CpxA mutant (L168del) also commonly occurs in nature. K. pneumoniae containing CpxA variants showed different colonization potentials through altered type 3 fimbriae expression. Lastly, we demonstrated that CpxA contributes to amino acid sensing, thus regulating the colonization of K. pneumoniae both on solid surfaces and in mouse intestines. The polymorphism of CpxA may help to broaden the environmental adaptation of the bacterium. These findings together reveal a Cpx-mediated regulation to diversify intestinal colonization in K. pneumoniae.

Mycobacterium abscessus, a fast-growing, non-tuberculous mycobacterium resistant to most antimicrobial drugs, causes a wide range of serious infections in humans, posing a significant public health challenge. The development of effective genetic manipulation tools for M. abscessus is still in progress, limiting both research and therapeutic advancements. However, the clustered regularly interspaced short palindromic repeats (CRISPR)-associated protein (Cas) systems have emerged as promising tools for generating highly specific double-strand breaks (DSBs) in its genome. One of the mechanisms that repair these DSBs is the error-prone nonhomologous end-joining (NHEJ) pathway, which facilitates targeted gene editing. In this study, we introduced a novel application of the CRISPR-NHEJ approach in M. abscessus. We demonstrated that NrgA from M. marinum plays a crucial role in repairing DSBs induced by the CRISPR-Cas system in M. abscessus. Contrary to previous findings, our study also revealed that inhibiting or overexpressing components of homologous recombination/single-strand annealing significantly reduces the efficiency of NHEJ repair in M. abscessus. This discovery challenges current perspectives and suggests that NHEJ repair in M. abscessus may involve components from both homologous recombination and single-strand annealing pathways, highlighting the complex interactions among the three DSB repair mechanisms in M. abscessus.

Transmembrane alkane monooxygenase (AlkB)-type monooxygenases, especially AlkB2 monooxygenases, are crucial for aerobic degradation of the medium-to-long-chain n-alkanes in hydrocarbon-utilizing microorganisms. In this study, we identified a GntR/VanR transcription regulator AlkR of Pseudomonas aeruginosa SJTD-1 involved in the negative regulation of AlkB2 and deciphered its nature of DNA binding and ligand release. The deletion of alkR enhanced the transcription levels of the alkB2 gene and the utilization efficiency of the medium-to-long-chain n-alkanes by strain SJTD-1. The dimer of AlkR recognizes and binds to a conserved palindromic motif in the promoter of the alkB2 gene, and structural symmetry is vital for DNA binding and transcription repression. The long-chain fatty acyl coenzyme A compounds can release AlkR and stimulate transcription of alkB2, reflecting the effect of alkane catabolic metabolites. Structural insights unveiled that the arginine residues and scaffold residues of AlkR are critical for DNA binding. Further bioinformatics analysis of AlkR revealed the widespread VanR-AlkB couples distributed in Pseudomonadaceae with high conservation in the sequences of functional genes and intergenic regions, highlighting a conserved regulatory pattern for n-alkane utilization across this family. These findings demonstrate the regulatory mechanism and structural basis of GntR/VanR transcription regulators in modulating n-alkane biodegradation and provide valuable insights in improving the bioremediation efficiency of hydrocarbon pollution.

The caseinolytic protease complex ClpP1P2 is crucial for protein homeostasis in mycobacteria and stress response and virulence of the pathogens. Its role as a potential drug target for combating tuberculosis (TB) has just begun to be substantiated in drug discovery research. We conducted a biochemical screening targeting the ClpP1P2 using a library of compounds phenotypically active against Mycobacterium tuberculosis (Mtb). The screening identified a phenyl ester compound GDI-5755, inhibiting the growth of Mtb and M. bovis BCG, the model organism of mycobacteria. GDI-5755 covalently modified the active-site serine residue of ClpP1, rendering the peptidase inactive, which was delineated through protein mass spectrometry and kinetic analyses. GDI-5755 exerted antibacterial activity by inhibiting ClpP1P2 in the bacteria, which could be demonstrated through a minimum inhibitory concentration (MIC) shift assay with a clpP1 CRISPRi knockdown (clpP1-KD) mutant GH189. The knockdown also remarkably heightened the mutant's sensitivity to ethionamide and meropenem, but not to many other TB drugs. On the other hand, a comparative proteomic analysis of wild-type cells exposed to GDI-5755 revealed the dysregulated proteome, specifically showing changes in the expression levels of multiple TB drug targets, including EthA, Ldt_Mt2, and PanD. Subsequent evaluation confirmed the synergistic activity of GDI-5755 when combined with the TB drugs to inhibit mycobacterial growth. Our findings indicate that small-molecule inhibitors targeting ClpP1P2, when used alongside existing TB medications, could represent novel therapeutic strategies.

Dissolved organic matter (DOM) contains thousands of molecules and is key for biogeochemical cycles in aquatic and terrestrial ecosystems by interacting with microbes. Over the last decade, the study of DOM has been advanced and accelerated with the developments of instrumental and statistical approaches. However, it is still challenging in statistical analyses, data visualization, and theoretical interpretations largely due to the complexity of molecular composition and underlying ecological mechanisms. In this study, we developed an R package iDOM with functions for the basic and advanced statistical analyses and the visualization of DOM derived from Fourier transform ion cyclotron resonance mass spectrometer (FT-ICR MS). The package could handle various data types of DOM, including molecular compositional data, molecular traits, and uncharacterized molecules (i.e., dark matter). It could integrate explanatory data, such as environmental and microbial data, to explore the relationships between DOM and abiotic or biotic drivers. To illustrate its use, we presented case studies with an example dataset of DOM and microbial communities under experimental warming. We included case studies of basic functions for the calculation of molecular traits, the assignment of molecular classes, and the compositional analyses of chemical diversity and dissimilarity. We further showed the case studies with advanced functions to quantify DOM assembly processes, assess the effects of dark matter on molecular interactions, analyze the ecological networks between DOM and microbes, and explore their response to warming. The source code and example dataset of iDOM are publicly available on https://github.com/jianjunwang/iDOM. We expect that iDOM will serve as a comprehensive pipeline for DOM statistical analyses and bridge the gap between chemical characterization and ecological interpretation in a theoretical framework.

[This corrects the article DOI: 10.1002/mlf2.12045.].

Spindle-shaped viruses exclusively infect archaea. Fuselloviruses represent a large group of spindle-shaped viruses and infect hyperthermophilic archaea of the order Sulfolobales. Although the first fusellovirus was identified nearly 40 years ago, the mechanism of host infection by these viruses remains poorly understood. Here, we show that SSV19, a fusellovirus isolated from a hot spring in the Philippines, is capable of hydrolyzing the host cell surface glycan identified as a heptasaccharide chain of QuiS₁Hex₄HexNAc₂. Our findings provide significant insights into the molecular strategy of host recognition and, possibly, entry by an archaeal virus.

Biosynthesis-a process utilizing biological systems to synthesize chemical compounds-has emerged as a revolutionary solution to 21st-century challenges due to its environmental sustainability, scalability, and high stereoselectivity and regioselectivity. Recent advancements in artificial intelligence (AI) are accelerating biosynthesis by enabling intelligent design, construction, and optimization of enzymatic reactions and biological systems. We first introduce the molecular retrosynthesis route planning in biochemical pathway design, including single-step retrosynthesis algorithms and AI-based chemical retrosynthesis route design tools. We highlight the advantages and challenges of large language models in addressing the sparsity of chemical data. Furthermore, we review enzyme discovery methods based on sequence and structure alignment techniques. Breakthroughs in AI-based structural prediction methods are expected to significantly improve the accuracy of enzyme discovery. We also summarize methods for de novo enzyme generation for nonnatural or orphan reactions, focusing on AI-based enzyme functional annotation and enzyme discovery techniques based on reaction or small molecule similarity. Turning to enzyme engineering, we discuss strategies to improve enzyme thermostability, solubility, and activity, as well as the applications of AI in these fields. The shift from traditional experiment-driven models to data-driven and computationally driven intelligent models is already underway. Finally, we present potential challenges and provide a perspective on future research directions. We envision expanded applications of biocatalysis in drug development, green chemistry, and complex molecule synthesis.

[This corrects the article DOI: 10.1002/mlf2.12154.].

[This corrects the article DOI: 10.1002/mlf2.12049.].