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BackgroundHeterologous booster vaccines are more effective than homologous booster vaccines in combating the coronavirus disease 2019 (COVID-19) outbreak. However, our understanding of homologous and heterologous booster vaccines for COVID-19 remains limited.MethodsWe recruited 34 healthy participants from two cohorts who were primed with two-dose inactivated COVID-19 vaccine before, vaccinated with COVID-19 inactivated vaccine and adenovirus-vectored vaccine (intramuscular and aerosol inhalation of Ad5-nCoV) as a third booster dose. We assessed the immune responses of participants before and 14 days after vaccination, including levels of neutralizing antibodies, IgG, and cytokines, and quantified the transcriptional profile of peripheral blood mononuclear cells (PBMCs).ResultsThe Ad5-nCoV group showed a significantly higher neutralizing antibody geometric mean titer (GMT) compared to the ICV group after 14 days of heterologous boosting. The intramuscular Ad5-nCoV group had a GMT of 191.8 (95% CI 129.0, 285.1) compared to 38.1 (95% CI 23.1, 62.8) in the ICV1 group (p

IntroductionSince its outbreak in December 2019, SARS-CoV-2 has spread rapidly across the world, posing significant threats and challenges to global public health. SARS-CoV-2, together with SARS-CoV and MERS-CoV, is a highly pathogenic coronavirus that contributes to fatal pneumonia. Understanding the similarities and differences at the transcriptome level between SARS-CoV-2, SARS-CoV, as well as MERS-CoV is critical for developing effective strategies against these viruses.MethodsIn this article, we comparatively analyzed publicly available transcriptome data of human cell lines infected with highly pathogenic SARS-CoV-2, SARS-CoV, MERS-CoV, and lowly pathogenic HCoV-229E. The host gene expression profiles during human coronavirus (HCoV) infections were generated, and the pathways and biological functions involved in immune responses, antiviral efficacy, and organ damage were intensively elucidated.ResultsOur results indicated that SARS-CoV-2 induced a stronger immune response versus the other two highly pathogenic HCoVs. Specifically, SARS-CoV-2 induced robust type I and type III IFN responses, marked by higher upregulation of type I and type III IFNs, as well as numerous interferon-stimulated genes (ISGs). Further Ingenuity Pathway Analysis (IPA) revealed the important role of ISGs for impeding SARS-CoV-2 infection, and the interferon/ISGs could be potential targets for therapeutic interventions. Moreover, our results uncovered that SARS-CoV-2 infection was linked to an enhanced risk of multi-organ toxicity in contrast to the other two highly pathogenic HCoVs.DiscussionThese findings provided valuable insights into the pathogenic mechanism of SARS-CoV-2, which showed a similar pathological feature but a lower fatality rate compared to SARS-CoV and MERS-CoV.

Providencia as an opportunistic pathogen can cause serious infection, and moreover the emergence of multi-drug-resistant Providencia strains poses a potentially life-threatening risk to public health. However, a comprehensive genomic study to reveal the population structure and dissemination of Providencia is still lacking. In this study, we conducted a genomic epidemiology analysis on the 580 global sequenced Providencia isolates, including 257 ones sequenced in this study (42 ones were fully sequenced). We established a genome sequence-based species classification scheme for Providencia, redefining the conventional 11 Providencia species into seven genocomplexes that were further divided into 18 genospecies, providing an extensively updated reference for Providencia species discrimination based on the largest Providencia genome dataset to date. We then dissected the profile of antimicrobial resistance genes and the prevalence of multi-drug-resistant Providencia strains among these genocomplexes/genospecies, disclosing the presence of diverse and abundant antimicrobial resistance genes and high resistance ratios against multiple classes of drugs in Providencia. We further dissected the genetic basis for the spread of blaNDM-1 in Providencia. blaNDM-1 genes were mainly carried by five incompatible (Inc) groups of plasmids: IncC, IncW, IncpPROV114-NR, IncpCHS4.1-3, and IncpPrY2001, and the last three were newly designated in this study. By tracking the spread of blaNDM-1-carrying plasmids, IncC, IncpPROV114-NR, IncpCHS4.1-3, and IncpPrY2001 plasmids were found to be highly involved in parallel horizontal transfer or vertical clonal expansion of blaNDM-1 among Providencia. Overall, our study provided a comprehensive genomic view of species differentiation, antimicrobial resistance prevalence, and plasmid-mediated blaNDM-1 dissemination in Providencia.

BackgroundTuberculosis (TB) remains a major global health concern, ranking as the second most lethal infectious disease following COVID-19. Smear-Negative Pulmonary Tuberculosis (SNPT) and Smear-Positive Pulmonary Tuberculosis (SPPT) are two common types of pulmonary tuberculosis characterized by distinct bacterial loads. To date, the precise molecular mechanisms underlying the differences between SNPT and SPPT patients remain unclear. In this study, we aimed to utilize proteomics analysis for identifying specific protein signatures in the plasma of SPPT and SNPT patients and further elucidate the molecular mechanisms contributing to different disease pathogenesis.MethodsPlasma samples from 27 SPPT, 37 SNPT patients and 36 controls were collected and subjected to TMT-labeled quantitative proteomic analyses and targeted GC-MS-based lipidomic analysis. Ingenuity Pathway Analysis (IPA) was then performed to uncover enriched pathways and functionals of differentially expressed proteins.ResultsProteomic analysis uncovered differential protein expression profiles among the SPPT, SNPT, and Ctrl groups, demonstrating dysfunctional immune response and metabolism in both SPPT and SNPT patients. Both groups exhibited activated innate immune responses and inhibited fatty acid metabolism, but SPPT patients displayed stronger innate immune activation and lipid metabolic inhibition compared to SNPT patients. Notably, our analysis uncovered activated antigen-presenting cells (APCs) in SNPT patients but inhibited APCs in SPPT patients, suggesting their critical role in determining different bacterial loads/phenotypes in SNPT and SPPT. Furthermore, some specific proteins were detected to be involved in the APC activation/acquired immune response, providing some promising therapeutic targets for TB.ConclusionOur study provides valuable insights into the differential molecular mechanisms underlying SNPT and SPPT, reveals the critical role of antigen-presenting cell activation in SNPT for effectively clearing the majority of Mtb in bodies, and shows the possibility of APC activation as a novel TB treatment strategy.

IntroductionNon-tuberculous mycobacteria (NTM) is a major category of environmental bacteria in nature that can be divided into rapidly growing mycobacteria (RGM) and slowly growing mycobacteria (SGM) based on their distinct growth rates. To explore differential molecular mechanisms between RGM and SGM is crucial to understand their survival state, environmental/host adaptation and pathogenicity. Comparative genomic analysis provides a powerful tool for deeply investigating differential molecular mechanisms between them. However, large-scale comparative genomic analysis between RGM and SGM is still uncovered.MethodsIn this study, we screened 335 high-quality, non-redundant NTM genome sequences covering 187 species from 3,478 online NTM genomes, and then performed a comprehensive comparative genomic analysis to identify differential genomic characteristics and featured genes/protein domains between RGM and SGM.ResultsOur findings reveal that RGM has a larger genome size, more genes, lower GC content, and more featured genes/protein domains in metabolism of some main substances (e.g. carbohydrates, amino acids, nucleotides, ions, and coenzymes), energy metabolism, signal transduction, replication, transcription, and translation processes, which are essential for its rapid growth requirements. On the other hand, SGM has a smaller genome size, fewer genes, higher GC content, and more featured genes/protein domains in lipid and secondary metabolite metabolisms and cellular defense mechanisms, which help enhance its genome stability and environmental adaptability. Additionally, orthogroup analysis revealed the important roles of bacterial division and bacteriophage associated genes in RGM and secretion system related genes for better environmental adaptation in SGM. Notably, PCoA analysis of the top 20 genes/protein domains showed precision classification between RGM and SGM, indicating the credibility of our screening/classification strategies.DiscussionOverall, our findings shed light on differential underlying molecular mechanisms in survival state, adaptation and pathogenicity between RGM and SGM, show the potential for our comparative genomic pipeline to investigate differential genes/protein domains at whole genomic level across different bacterial species on a large scale, and provide an important reference and improved understanding of NTM.

The rapid spread of carbapenemase-producing Klebsiella pneumoniae (cpKP) poses serious threats to public health; however, the underlying genetic basis for its dissemination is still unknown. We conducted a comprehensive genomic epidemiology analysis on 420 cpKP isolates collected from 70 hospitals in 24 provinces/autonomous regions/municipalities of China during 2009–2017 by short-/long-read sequencing. The results showed that most cpKP isolates were categorized into clonal group 258 (CG258), in which ST11 was the dominant clone. Phylogenetic analysis revealed three major clades including the top one of Clade 3 for CG258 cpKP isolates. Additionally, carbapenemase gene analysis indicated that blaKPC was dominant in the cpKP isolates, and most blaKPC genes were located in five major incompatibility (Inc) groups of blaKPC-harboring plasmids. Importantly, three advantageous combinations of host–blaKPC-carrying plasmid (Clade 3.1+3.2–IncFIIpHN7A8, Clade 3.1+3.2–IncFIIpHN7A8:IncR, and Clade 3.3–IncFIIpHN7A8:IncpA1763-KPC) were identified to confer cpKP isolates the advantages in both genotypes (strong correlation/coevolution) and phenotypes (resistance/growth/competition) to facilitate the nationwide spread of ST11/CG258 cpKP. Intriguingly, Bayesian skyline analysis illustrated that the three advantageous combinations might be directly associated with the strong population expansion during 2007–2008 and subsequent maintenance of the population of ST11/CG258 cpKP after 2008. We then examined drug resistance profiles of these cpKP isolates and proposed combination treatment regimens for CG258/non-CG258 cpKP infections. Thus, the findings of our systematical analysis shed light on the molecular epidemiology and genetic basis for the dissemination of ST11/CG258 cpKP in China, and much emphasis should be given to the close monitoring of advantageous cpKP–plasmid combinations.

Abstract Diffuse alveolar damage (DAD) triggers neutrophilic inflammation in damaged tissues of the lung, but little is known about the distinct roles of tissue structural cells in modulating the recruitment of neutrophils to damaged areas. Here, by combining single‐cell and spatial transcriptomics, and using quantitative assays, we systematically analyze inflammatory cell states in a mouse model of DAD‐induced neutrophilic inflammation after aerosolized intratracheal inoculation with ricin toxin. We show that homeostatic resident fibroblasts switch to a hyper‐inflammatory state, and the subsequent occurrence of a CXCL1‐CXCR2 chemokine axis between activated fibroblasts (AFib) as the signal sender and neutrophils as the signal receiver triggers further neutrophil recruitment. We also identify an anatomically localized inflamed niche (characterized by a close‐knit spatial intercellular contact between recruited neutrophils and AFib) in peribronchial regions that facilitate the pulmonary inflammation outbreak. Our findings identify an intricate interplay between hyper‐inflammatory fibroblasts and neutrophils and provide an overarching profile of dynamically changing inflammatory microenvironments during DAD progression.

Abstract Background Tuberculosis (TB) had been the leading lethal infectious disease worldwide for a long time (2014–2019) until the COVID-19 global pandemic, and it is still one of the top 10 death causes worldwide. One important reason why there are so many TB patients and death cases in the world is because of the difficulties in precise diagnosis of TB using common detection methods, especially for some smear-negative pulmonary tuberculosis (SNPT) cases. The rapid development of metabolome and machine learning offers a great opportunity for precision diagnosis of TB. However, the metabolite biomarkers for the precision diagnosis of smear-positive and smear-negative pulmonary tuberculosis (SPPT/SNPT) remain to be uncovered. In this study, we combined metabolomics and clinical indicators with machine learning to screen out newly diagnostic biomarkers for the precise identification of SPPT and SNPT patients. Methods Untargeted plasma metabolomic profiling was performed for 27 SPPT patients, 37 SNPT patients and controls. The orthogonal partial least squares-discriminant analysis (OPLS-DA) was then conducted to screen differential metabolites among the three groups. Metabolite enriched pathways, random forest (RF), support vector machines (SVM) and multilayer perceptron neural network (MLP) were performed using Metaboanalyst 5.0, “caret” R package, “e1071” R package and “Tensorflow” Python package, respectively. Results Metabolomic analysis revealed significant enrichment of fatty acid and amino acid metabolites in the plasma of SPPT and SNPT patients, where SPPT samples showed a more serious dysfunction in fatty acid and amino acid metabolisms. Further RF analysis revealed four optimized diagnostic biomarker combinations including ten features (two lipid/lipid-like molecules and seven organic acids/derivatives, and one clinical indicator) for the identification of SPPT, SNPT patients and controls with high accuracy (83–93%), which were further verified by SVM and MLP. Among them, MLP displayed the best classification performance on simultaneously precise identification of the three groups (94.74%), suggesting the advantage of MLP over RF/SVM to some extent. Conclusions Our findings reveal plasma metabolomic characteristics of SPPT and SNPT patients, provide some novel promising diagnostic markers for precision diagnosis of various types of TB, and show the potential of machine learning in screening out biomarkers from big data.

Klebsiella pneumoniae (K. pneumoniae) is an important pathogen that can cause severe hospital- and community-acquired infections. To systematically investigate its methylation features, we determined the whole-genome sequences of 14 K. pneumoniae strains covering varying serotypes, multilocus sequence types, clonal groups, viscosity/virulence, and drug resistance. Their methylomes were further characterized using Pacific Biosciences single-molecule real-time and bisulfite technologies. We identified 15 methylation motifs [13 N6-methyladenine (6mA) and two 5-methylcytosine (5mC) motifs], among which eight were novel. Their corresponding DNA methyltransferases were also validated. Additionally, we analyzed the genomic distribution of GATC and CCWGG methylation motifs shared by all strains, and identified differential distribution patterns of some hemi-/un-methylated GATC motifs, which tend to be located within intergenic regions (IGRs). Specifically, we characterized the in vivo methylation kinetics at single-base resolution on a genome-wide scale by simulating the dynamic processes of replication-mediated passive demethylation and MTase-catalyzed re-methylation. The slow methylation of the GATC motifs in the replication origin (oriC) regions and IGRs implicates the epigenetic regulation of replication initiation and transcription. Our findings illustrate the first comprehensive dynamic methylome map of K. pneumoniae at single-base resolution, and provide a useful reference to better understand epigenetic regulation in this and other bacterial species.

ABSTRACT The emergence of a new type of COVID-19 patients, who were retested positive after hospital discharge with long-term persistent SARS-CoV-2 infection but without COVID-19 clinical symptoms (hereinafter, LTPPs), poses novel challenges to COVID-19 treatment and prevention. Why was there such a contradictory phenomenon in LTPPs? To explore the mechanism underlying this phenomenon, we performed quantitative proteomic analyses using the sera of 12 LTPPs (Wuhan Pulmonary Hospital), with the longest carrying history of 132 days, and mainly focused on 7 LTPPs without hypertension (LTPPs-NH). The results showed differential serum protein profiles between LTPPs/LTPPs-NH and health controls. Further analysis identified 174 differentially-expressed-proteins (DEPs) for LTPPs, and 165 DEPs for LTPPs-NH, most of which were shared. GO and KEGG analyses for these DEPs revealed significant enrichment of “coagulation” and “immune response” in both LTPPs and LTPPs-NH. A unity of contradictory genotypes in the 2 aspects were then observed: some DEPs showed the same dysregulated expressed trend as that previously reported for patients in the acute phase of COVID-19, which might be caused by long-term stimulation of persistent SARS-CoV-2 infection in LTPPs, further preventing them from complete elimination; in contrast, some DEPs showed the opposite expression trend in expression, so as to retain control of COVID-19 clinical symptoms in LTPPs. Overall, the contrary effects of these DEPs worked together to maintain the balance of LTPPs, further endowing their contradictory steady-state with long-term persistent SARS-CoV-2 infection but without symptoms. Additionally, our study revealed some potential therapeutic targets of COVID-19. Further studies on these are warranted. IMPORTANCE This study reported a new type of COVID-19 patients and explored the underlying molecular mechanism by quantitative proteomic analyses. DEPs were significantly enriched in “coagulation” and “immune response”. Importantly, we identified 7 “coagulation system”- and 9 “immune response”-related DEPs, the expression levels of which were consistent with those previously reported for patients in the acute phase of COVID-19, which appeared to play a role in avoiding the complete elimination of SARS-CoV-2 in LTPPs. On the contrary, 6 “coagulation system”- and 5 “immune response”-related DEPs showed the opposite trend in expression. The 11 inconsistent serum proteins seem to play a key role in the fight against long-term persistent SARS-CoV-2 infection, further retaining control of COVID-19 clinical symptom of LTPPs. The 26 proteins can serve as potential therapeutic targets and are thus valuable for the treatment of LTPPs; further studies on them are warranted.

Summary Non‐tuberculous mycobacteria (NTM) can cause various respiratory diseases and even death in severe cases, and its incidence has increased rapidly worldwide. To date, it’s difficult to use routine diagnostic methods and strain identification to precisely diagnose various types of NTM infections. We combined systematic comparative genomics with machine learning to select new diagnostic markers for precisely identifying five common pathogenic NTMs (Mycobacterium kansasii, Mycobacterium avium, Mycobacterium intracellular, Mycobacterium chelonae, Mycobacterium abscessus). A panel including six genes and two SNPs (nikA, benM, codA, pfkA2, mpr, yjcH, rrl C2638T, rrl A1173G) was selected to simultaneously identify the five NTMs with high accuracy (> 90%). Notably, the panel only containing the six genes also showed a good classification effect (accuracy > 90%). Additionally, the two panels could precisely differentiate the five NTMs from M. tuberculosis (accuracy > 99%). We also revealed some new marker genes/SNPs/combinations to accurately discriminate any one of the five NTMs separately, which provided the possibility to diagnose one certain NTM infection precisely. Our research not only reveals novel promising diagnostic markers to promote the development of precision diagnosis in NTM infectious, but also provides an insight into precisely identifying various genetically close pathogens through comparative genomics and machine learning.

As a newly emerging Klebsiella pathogen, more and more Klebsiella michiganensis drug resistant strains have been reported in recent years, which posed serious threats to public health. Here we first reported a multidrug-resistant K. michiganensis strain 12084 with two blaSIM-1 and one mcr-9.2 genes isolated from the sputum specimen of a patient in the Second Affiliated Hospital of Zhejiang University School of Medicine and analyzed its genetic basis and drug-resistance phenotypes. Genetic analysis showed that this strain harbored three different incompatibility groups (IncHI2, IncHI5, and IncFIIpKPHS2:IncFIB-4.1) of plasmids (p12084-HI2, p12084-HI5, and p12084-FII). A total of 26 drug-resistance genes belonging to 12 classes of antibiotics were identified, most of which (24) were located on two plasmids (p12084-HI2 and p12084-HI5). Interestingly, two blaSIM-1 genes were identified to locate on p12084-HI2 and p12084-HI5, respectively, both of which were embedded in In630, indicating their genetic homogeny. It was noting that one blaSIM-1 gene was situated in a novel unit transposon (referred to as Tn6733) on the p12084-HI5 plasmid. We also discovered an mcr-9.2 gene on the p12084-HI2 plasmid. To the best of our knowledge, this is the first report of a blaSIM-1 and mcr-9.2 harboring K. michiganensis strain. We then investigated the population structure/classification, and antibiotic resistance for all 275 availably global K. michiganensis genomes. Population structure revealed that K. michiganensis could be divided into two main clades (Clade 1 and Clade 2); the most popular ST29 was located in Clade 1, while other common STs (such as ST50, ST27, and ST43) were located in Clade 2. Drug-resistance analysis showed 25.5% of the K. michiganensis strains (70/275) harboring at least one carbapenemase gene, indicating severe drug resistance of K. michiganensis beyond our imagination; this is a dangerous trend and should be closely monitored, especially for ST27 K. michiganensis with the most drug-resistant genes among all the STs. Overall, we reported a blaSIM-1 and mcr-9.2 harboring K. michiganensis strain, and further revealed the population structure/classification, and drug-resistance of K. michiganensis, which provided an important framework, reference, and improved understanding of K. michiganensis.

Objective: We investigated the pathogenesis of a patient with severe acute pancreatitis by comprehensively analysing a rare carbapenem-resistant hypervirulent K1/ST1265 Klebsiella pneumoniae (CR-HvKP) strain. Methods: We conducted virulence and multidrug-resistance phenotypic characterization and identified a CR-HvKP strain from the patient. It was subjected to Pacbio sequencing, and subsequent analysis of virulence, resistance genes and mobile genetic elements. Results: We described the phenotype and genotype of a rare CR-HvKP strain with an untypeable blaKPC-harboured conjugative plasmid and a pLVPK-like virulent plasmid. Resistance gene analysis showed that the untypeable blaKPC-2-harboured plasmid was formed by IS26-mediated recombination of blaKPC-embedded transposon Tn6500 into pCN061p4 from Escherichia coli. Interestingly, it had an R-M system that might protect plasmid from cleavage. This may facilitate the stabilization of plasmids in bacteria in the event of missing CR-plasmid during transmission. Virulence gene analysis indicated 78 virulence genes on the genome, including 67 on the chromosome (37 in high-pathogenic island) and 11 on the pLVPK-like virulence plasmid (harbouring rmpA/rmpA2). Further phylogenetic analysis revealed that the CR-HvKP evolved from HvKP through acquiring an antimicrobial-resistance plasmid. Conclusion: Our research, to our knowledge, first reported a ST1265/K1 CR-HvKP strain with an untypeable blaKPC-harboured plasmid. The trend that HvKP could evolve into CR-HvKP by obtaining stabilized/conjugative blaKPC-carrying plasmids is a considerable threat to public health and should be closely supervised.

Around 9% of the adult population in the world (463 million) suffer from diabetes mellitus. Most of them (~90%) belong to type 2 diabetes mellitus (T2DM), which is a common chronic metabolic disorder, and the number of cases has been reported to increase each year. Zucker diabetic fatty (ZDF) rat provides a successful animal model to study the pathogenesis of T2DM. Although previous hepatic transcriptome studies revealed some novel genes associated with the occurrence and development of T2DM, there still lacks the comprehensive transcriptomic analysis for the liver tissues of ZDF rats. We performed comparative transcriptome analyses between the liver tissues of ZDF rats and healthy ZCL rats and also evaluated several clinical indices. We could identify 214 and 104 differentially expressed genes (DEGs) and lncRNAs in ZDF rats, respectively. Pathway and biofunction analyses showed a synergistic effect between mRNAs and lncRNAs. By comprehensively analyzing transcriptomic data and clinical indices, we detected some typical features of T2DM in ZDF rats, such as upregulated metabolism (significant increased lipid absorption/transport/utilization, gluconeogenesis, and protein hydrolysis), increased inflammation, liver injury and increased endoplasmic reticulum (ER) stress. In addition, of the 214 DEGs, 114 were known and 100 were putative T2DM-related genes, most of which have been associated with substance metabolism (particularly degradation), inflammation, liver injury and ER stress biofunctions. Our study provides an important reference and improves understanding of molecular pathogenesis of obesity-associated T2DM. Our data can also be used to identify potential diagnostic markers and therapeutic targets, which should strengthen the prevention and treatment of T2DM.

Tuberculosis (TB) has been the leading lethal infectious disease worldwide since 2014, and about one third of the world’s population has a latent TB infection (LTBI). This is largely attributed to the difficulties in diagnosis and treatment of TB and LTBI patients. Exosomes offer a new perspective on investigation of the process of TB infection. In this study, we performed small RNA sequencing to explore small RNA profiles of serum exosomes derived from LTBI and TB patients and healthy controls (HC). Our results revealed distinct miRNA profile of the exosomes in the three groups. We screened 250 differentially expressed miRNAs including 130 specifically expressed miRNAs. Some miRNAs were further validated to be specifically expressed in LTBI (hsa-let-7e-5p, hsa-let-7d-5p, hsa-miR-450a-5p, and hsa-miR-140-5p) and TB samples (hsa-miR-1246, hsa-miR-2110, hsa-miR-370-3P, hsa-miR-28-3p, and hsa-miR-193b-5p). Additionally, we demonstrated four expression panels in LTBI and TB groups, and six expression patterns among the three groups. These specifically expressed miRNAs and differentially expressed miRNAs in different panels and patterns provide potential biomarkers for detection/diagnosis of latent and active TB using exosomal miRNAs. Additionally, we also discovered plenty of small RNAs derived from genomic repetitive sequences, which might play roles in host immune responses along with Mtb infection progresses. Overall, our findings provide important reference and an improved understanding about miRNAs and repetitive region-derived small RNAs in exosomes during the Mtb infectious process, and facilitate the development of potential molecular targets for detection/diagnosis of latent and active tuberculosis.

Tuberculosis (TB) has surpassed HIV as the leading infectious disease killer worldwide since 2014. The main pathogen, Mycobacterium tuberculosis (Mtb), contains ~4,000 genes that account for ~90% of the genome. However, it is still unclear which of these genes are primary/secondary, which are responsible for generality/individuality, and which interconvert during evolution. Here we utilized a pan-genomic analysis of 36 Mtb genomes to address these questions. We identified 3,679 Mtb core (i.e., primary) genes, determining their phenotypic generality (e.g., virulence, slow growth, dormancy). We also observed 1,122 dispensable and 964 strain-specific secondary genes, reflecting partially shared and lineage-/strain-specific individualities. Among which, five L2 lineage-specific genes might be related to the increased virulence of the L2 lineage. Notably, we discovered 28 Mtb “Super Core Genes” (SCGs: more than a copy in at least 90% strains), which might be of increased importance, and reflected the “super phenotype generality.” Most SCGs encode PE/PPE, virulence factors, antigens, and transposases, and have been verified as playing crucial roles in Mtb pathogenicity. Further investigation of the 28 SCGs demonstrated the interconversion among SCGs, single-copy core, dispensable, and strain-specific genes through copy number variations (CNVs) during evolution; different mutations on different copies highlight the delicate adaptive-evolution regulation amongst Mtb lineages. This reflects that the importance of genes varied through CNVs, which might be driven by selective pressure from environment/host-adaptation. In addition, compared with Mycobacterium bovis (Mbo), Mtb possesses 48 specific single core genes that partially reflect the differences between Mtb and Mbo individuality.

Tuberculosis (TB) has exceeded HIV as the most lethal infectious disease globally for two consecutive years. Moreover, one third of the world’s population is estimated to have latent tuberculosis infection (LTBI). This is mainly because of difficulties associated with diagnosis and treatment for both TB and LTBI patients. Exosomes provide a promising research tool for TB diagnosis and treatment because they are released from various cells containing valuable biochemical information related to disease. In this study, we performed RNA-sequencing analysis on exosomes derived from clinical specimens of healthy controls (HC), active tuberculosis (ATB), and LTBI patients. Our results revealed the distinct gene expression profiles of the exosomes from LTBI and ATB patients. (1) We identified many distinct up-regulated and down-regulated differentially expressed genes (DEGs) in LTBI and ATB samples, and further screened the top-20 DEGs which might provide a potential panel for differentiation of HC, LTBI, and ATB. (2) We classified all the DEGs into six expression patterns, screened the top-20 genes in each pattern, and mainly focused on those highly expressed in LTBI and ATB. (3) Some Mycobacterium tuberculosis (Mtb) RNAs were only enriched in the exosomes of LTBI samples. (4) Pathway and function analysis further indicated down-regulated signaling pathways/immune response and up-regulated apoptosis/necrosis. Our findings indicate the selective packaging of RNA cargoes into exosomes under different stages of Mtb infection, while facilitating the development of potential targets for the diagnosis, prevention and treatment of tuberculosis.

Background: Tuberculosis (TB) remains a major global health concern, ranking as the second most lethal infectious disease following COVID-19. Smear-Negative Pulmonary Tuberculosis (SNPT) and Smear-Positive Pulmonary Tuberculosis (SPPT) are two common types of pulmonary tuberculosis characterized by distinct bacterial loads. To date, the precise molecular mechanisms underlying the differences between SNPT and SPPT patients remain unclear. In this study, we aimed to utilize proteomics analysis for identifying specific protein signatures in the plasma of SPPT and SNPT patients and further elucidate the molecular mechanisms contributing to different disease pathogenesis. Methods: Plasma samples from 27 SPPT, 37 SNPT patients and 36 controls were collected and subjected to TMT-labeled quantitative proteomic analyses and targeted GC-MS-based lipidomic analysis. Ingenuity Pathway Analysis (IPA) was then performed to uncover enriched pathways and functionals of differentially expressed proteins. Results: Proteomic analysis uncovered differential protein expression profiles among the SPPT, SNPT, and Ctrl groups, demonstrating dysfunctional immune response and metabolism in both SPPT and SNPT patients. Both groups exhibited activated innate immune responses and inhibited fatty acid metabolism, but SPPT patients displayed stronger innate immune activation and lipid metabolic inhibition compared to SNPT patients. Notably, our analysis uncovered activated antigen-presenting cells (APCs) in SNPT patients but inhibited APCs in SPPT patients, suggesting their critical role in determining different bacterial loads/phenotypes in SNPT and SPPT. Furthermore, some specific proteins were detected to be involved in the APC activation/acquired immune response, providing some promising therapeutic targets for TB. Conclusion: Our study provides valuable insights into the differential molecular mechanisms underlying SNPT and SPPT, reveals the critical role of antigenpresenting cell activation in SNPT for effectively clearing the majority of Mtb in bodies, and shows the possibility of APC activation as a novel TB treatment strategy. [ABSTRACT FROM AUTHOR]

As a newly emerging Klebsiella pathogen, more and more Klebsiella michiganensis drug resistant strains have been reported in recent years, which posed serious threats to public health. Here we first reported a multidrug-resistant K. michiganensis strain 12084 with two blaSIM-1 and one mcr-9.2 genes isolated from the sputum specimen of a patient in the Second Affiliated Hospital of Zhejiang University School of Medicine and analyzed its genetic basis and drug-resistance phenotypes. Genetic analysis showed that this strain harbored three different incompatibility groups (IncHI2, IncHI5, and IncFIIpKPHS2:IncFIB-4.1) of plasmids (p12084-HI2, p12084-HI5, and p12084- FII). A total of 26 drug-resistance genes belonging to 12 classes of antibiotics were identified, most of which (24) were located on two plasmids (p12084-HI2 and p12084-HI5). Interestingly, two blaSIM-1 genes were identified to locate on p12084-HI2 and p12084-HI5, respectively, both of which were embedded in In630, indicating their genetic homogeny. It was noting that one blaSIM-1 gene was situated in a novel unit transposon (referred to as Tn6733) on the p12084- HI5 plasmid. We also discovered an mcr-9.2 gene on the p12084-HI2 plasmid. To the best of our knowledge, this is the first report of a blaSIM-1 and mcr-9.2 harboring K. michiganensis strain. We then investigated the population structure/classification, and antibiotic resistance for all 275 availably global K. michiganensis genomes. Population structure revealed that K. michiganensis could be divided into two main clades (Clade 1 and Clade 2); the most popular ST29 was located in Clade 1, while other common STs (such as ST50, ST27, and ST43) were located in Clade 2. Drug-resistance analysis showed 25.5% of the K. michiganensis strains (70/275) harboring at least one carbapenemase gene, indicating severe drug resistance of K. michiganensis beyond our imagination; this is a dangerous trend and should be closely monitored, especially for ST27 K. michiganensis with the most drug-resistant genes among all the STs. Overall, we reported a blaSIM-1 and mcr-9.2 harboring K. michiganensis strain, and further revealed the population structure/classification, and drug-resistance of K. michiganensis, which provided an important framework, reference, and improved understanding of K. michiganensis. [ABSTRACT FROM AUTHOR]

Polyvinyl alcohol (PVA) is used widely in industry, and associated environmental pollution is a serious problem. Herein, we report a novel, efficient PVA degrader, Stenotrophomonas rhizophila QL-P4, isolated from fallen leaves from a virgin forest in the Qinling Mountains. The complete genome was obtained using single-molecule real-time (SMRT) technology and corrected using Illumina sequencing. Bioinformatics analysis revealed eight PVA/vinyl alcohol oligomer (OVA)- degrading genes. Of these, seven genes were predicted to be involved in the classic intracellular PVA/OVA degradation pathway, and one (BAY15_3292) was identified as a novel PVA oxidase. Five PVA/OVA-degrading enzymes were purified and characterized. One of these, BAY15_1712, a PVA dehydrogenase (PVADH), displayed high catalytic efficiency toward PVA and OVA substrate. All reported PVADHs only have PVA-degrading ability. Most importantly, we discovered a novel PVA oxidase (BAY15_3292) that exhibited higher PVA-degrading efficiency than the reported PVADHs. Further investigation indicated that BAY15_3292 plays a crucial role in PVA degradation in S. rhizophila QL-P4. Knocking out BAY15_3292 resulted in a significant decline in PVA-degrading activity in S. rhizophila QL-P4. Interestingly, we found that BAY15_3292 possesses exocrine activity, which distinguishes it from classic PVADHs. Transparent circle experiments further proved that BAY15_3292 greatly affects extracellular PVA degradation in S. rhizophila QL-P4. The exocrine characteristics of BAY15_3292 facilitate its potential application to PVA bioremediation. In addition, we report three new efficient secondary alcohol dehydrogenases (SADHs) with OVA-degrading ability in S. rhizophila QL-P4; in contrast, only one OVA-degrading SADH was reported previously. IMPORTANCE With the widespread application of PVA in industry, PVA-related environmental pollution is an increasingly serious issue. Because PVA is difficult to degrade, it accumulates in aquatic environments and causes chronic toxicity to aquatic organisms. Biodegradation of PVA, as an economical and environment-friendly method, has attracted much interest. To date, effective and applicable PVA-degrading bacteria/enzymes have not been reported. Herein, we report a new efficient PVA degrader (S. rhizophila QL-P4) that has five PVA/OVA-degrading enzymes with high catalytic efficiency, among which BAY15_1712 is the only reported PVADH with both PVA- and OVA-degrading abilities. Importantly, we discovered a novel PVA oxidase (BAY15_3292) that is not only more efficient than other reported PVA-degrading PVADHs but also has exocrine activity. Overall, our findings provide new insight into PVA-degrading pathways in microorgan-isms and suggest S. rhizophila QL-P4 and its enzymes have the potential for application to PVA bioremediation to reduce or eliminate PVA-related environmental pollution. [ABSTRACT FROM AUTHOR]