p85α deficiency alleviates ischemia-reperfusion injury by promoting cardiomyocyte survival.

Myocardial ischemia-reperfusion (I/R) injury is a prevalent cause of myocardial injury, involving a series of interconnected pathophysiological processes. However, there is currently no clinical therapy for effectively mitigating myocardial I/R injury. Here, we show that p85α protein levels increase in response to I/R injury through a comprehensive analysis of cardiac proteomics, and confirm this in the I/R-injured murine heart and failing human myocardium. Genetic inhibition of p85α in mice activates the Akt-GSK3ß/Bcl-x(L) signaling pathway and ameliorates I/R-induced cardiac dysfunction, apoptosis, inflammation, and mitochondrial dysfunction. p85α silencing in cardiomyocytes alleviates hypoxia-reoxygenation (H/R) injury through activating the Akt-GSK3ß/Bcl-x(L) signaling pathway, while its overexpression exacerbates the damage. Mechanistically, the interaction between MG53 and p85α triggers the ubiquitination and degradation of p85α, consequently enhancing Akt phosphorylation and ultimately having cardioprotective effects. Collectively, our findings reveal that substantial reduction of p85α and subsequently activated Akt signaling have a protective effect against cardiac I/R injury, representing an important therapeutic strategy for mitigating myocardial damage.

Proteomic analyses of smear-positive/negative tuberculosis patients uncover differential antigen-presenting cell activation and lipid metabolism.

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 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.

Serum Proteomic Analysis for New Types of Long-Term Persistent COVID-19 Patients in Wuhan.

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.

[Application of metagenomic and culturomic technologies in fecal microbiota transplantation: a review].

Fecal microbiota transplantation (FMT) refers to using the intestinal microorganisms present in the feces or processed feces from healthy people for treating various types of diseases, such as digestive and metabolic diseases. The rapid development of metagenomic and culturomic technologies in gut microbiome analysis provides powerful tools for the FMT research and its clinical applications. Metagenomics technologies comprehensively revealed the diversity and functions of gut microbiota under health and disease conditions, while culturomics technologies helped isolation and identification of "unculturable" bacteria in the human gut under conventional culture conditions. The combination of these two technologies not only enabled us better understand the FMT regularities of cause and effect in clinical practices, but also effectively promoted its applications. Considering the above advantages, this article summarized the applications of metagenomics and culturomics technologies in FMT and prospected its future development trend.

A bla SIM-1 and mcr-9.2 harboring Klebsiella michiganensis strain reported and genomic characteristics of Klebsiella michiganensis.

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 bla SIM-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 bla SIM-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 bla SIM-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 bla SIM-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 bla SIM-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.

Combining metabolome and clinical indicators with machine learning provides some promising diagnostic markers to precisely detect smear-positive/negative pulmonary tuberculosis.

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.

Genomic Epidemiology of Carbapenemase-producing Klebsiella pneumoniae in China.

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.

Genomic insights into a complete deletion of the mgrB locus in colistin-resistant Klebsiella pneumoniae ST2268 isolated from a human infection.

OBJECTIVES: The emergence of colistin-resistant Klebsiella pneumoniae (CoRKp) is a serious public-health issue as colistin is the last line of defence against infections caused by multidrug-resistant Gram-negative bacteria. In this study, we generated a draft genome sequence for CoRKp strain P094-1 isolated from a sputum sample of an infected patient. METHODS: Whole genomic DNA of strain P094-1 was sequenced using a PacBio sequencing platform. Generated reads were de novo assembled using Hierarchical Genome Assembly Process (HGAP) v.3.0. Colistin resistance-related genes were predicted from the genome sequence and were validated experimentally. RESULTS: The genome of strain P094-1 lacked a 20.3-kb region, including complete deletion of the mgrB gene. Molecular and genome sequencing-based analyses revealed that the observed colistin resistance of P094-1 could not be attributed to plasmid-borne genes mcr-1 to mcr-9 or to alteration of the pmr and pho operons (deletions, insertions or substitutions), but was conferred by an insertion sequence 1 (IS1)-induced total deletion of mgrB. CONCLUSION: This is the first reported whole-genome sequence of an unusual CoRKp isolate containing an IS1-induced deletion of mgrB.

Profiling gene expression reveals insights into pulmonary response to aerosolized botulinum toxin type A exposure in mice.

Botulinum neurotoxin type A (BoNT/A) is traditional medicine and well known for its therapeutic use as an anesthetic and in cosmetic applications that work through the inhibition of acetylcholine exocytosis in neuronal cells. BoNT/A also has the potential to function as a biological weapon due to its high mortality rate and ease of dispersal. Emerging evidence suggests that BoNT/A exhibits biological effects on nonneuronal cells. In cytology experiments, BoNT/A induces global gene expression alterations. However, pulmonary effects from exposure to aerosolized BoNT/A have not been evaluated. This study investigated the global transcriptional profile of lung tissues after botulism inhalation. A mice model of inhaled botulism was established using intratracheal exposure to aerosolized BoNT/A and described through histological examination and flow cytometry. Transcriptomic analysis revealed that genes related to acute inflammatory responses were upregulated at 12-h postexposure. Increased expression of multiple anti-inflammatory marker genes and decreased expression of pro-inflammatory marker genes were observed at 48- to 72-h postexposure, underscoring a transcriptional shift toward a pro-reparative phenotype. Histological examination and cell proportions analysis mirrored these expression patterns. Accordingly, the orchestration of a quick phenotype transition prompted by BoNT/A may have the potential for promoting the resolution of the inflammatory lung. To our knowledge, this study represents the first research to investigate the pulmonary transcriptional responses of aerosolized BoNT/A exposure; the results may provide new insights in elucidating the molecular mechanism for pulmonary inhaled botulism and highlight the potential therapeutic application of BoNT/A in mitigating inflammatory conditions.

Systematic analysis of supervised machine learning as an effective approach to predicate ß-lactam resistance phenotype in Streptococcus pneumoniae.

Streptococcus pneumoniae is the most common human respiratory pathogen, and ß-lactam antibiotics have been employed to treat infections caused by S. pneumoniae for decades. ß-lactam resistance is steadily increasing in pneumococci and is mainly associated with the alteration in penicillin-binding proteins (PBPs) that reduce binding affinity of antibiotics to PBPs. However, the high variability of PBPs in clinical isolates and their mosaic gene structure hamper the predication of resistance level according to the PBP gene sequences. In this study, we developed a systematic strategy for applying supervised machine learning to predict S. pneumoniae antimicrobial susceptibility to ß-lactam antibiotics. We combined published PBP sequences with minimum inhibitory concentration (MIC) values as labelled data and the sequences from NCBI database without MIC values as unlabelled data to develop an approach, using only a fragment from pbp2x (750 bp) and a fragment from pbp2b (750 bp) to predicate the cefuroxime and amoxicillin resistance. We further validated the performance of the supervised learning model by constructing mutants containing the randomly selected pbps and testing more clinical strains isolated from Chinese hospital. In addition, we established the association between resistance phenotypes and serotypes and sequence type of S. pneumoniae using our approach, which facilitate the understanding of the worldwide epidemiology of S. pneumonia.

Five novel carbapenem-hydrolysing OXA-type ß-lactamase groups are intrinsic in Acinetobacter spp.

Objectives: Carbapenem resistance in Acinetobacter spp. is increasing and is primarily associated with the expression of OXA-type ß-lactamases. However, the role of intrinsic OXA-type ß-lactamases in the carbapenem resistance of Acinetobacter spp. has not been fully elucidated. The aim of this study was thus to understand this issue. Methods: We applied bioinformatic screening of putative blaOXA genes against available genome sequences. The putative blaOXA genes were cloned into pKFAb and expressed in Escherichia coli and Acinetobacter baumannii to determine their antibiotic susceptibility. blaOXA genes were knocked out in their native hosts using pEX18Gm. Results: Five novel groups of carbapenem-hydrolysing OXA-type ß-lactamases were identified in Acinetobacter rudis, Acinetobacter bohemicus, Acinetobacter tandoii, Acinetobacter gyllenbergii, Acinetobacter proteolyticus, Acinetobacter dispersus, Acinetobacter colistiniresistens and Acinetobacter guillouiae. The five OXA groups clustered into five highly supported monophyletic clades and are distinct from known OXA-type carbapenemases in the phylogenetic tree. Most of them conferred resistance to imipenem, meropenem, ertapenem, amoxicillin and ampicillin in E. coli and A. baumannii. The conserved location and prevalence of the blaOXA genes among the species suggest they are intrinsic. The blaOXA genes in A. rudis, A. guillouiae and A. gyllenbergii were knocked out separately and the blaOXA-665-deficient A. rudis and blaOXA-274-deficient A. guillouiae exhibited increased susceptibility to imipenem, meropenem, amoxicillin and ampicillin. Conclusions: Five novel intrinsic OXA groups were identified in the genus Acinetobacter and most of them can hydrolyse carbapenems. This study furthers our understanding of the wide distribution of carbapenem-hydrolysing OXA-type ß-lactamases in Acinetobacter spp.

Multichannel Dynamic Interfacial Printing: An Alternative Multicomponent Droplet Generation Technique for Lab in a Drop.

Generation of uniform emulsion droplets mixed with multiple components is one of the key issues in the field of lab in a drop. Traditionally, droplet microfluidic chips are often served as the prime choice while designing and fabricating microfluidic chips always rely on skilled technician and specialized equipment, severely restricting its wide accessibility. In this work, an alternative technique, called multichannel dynamic interfacial printing (MC-DIP), was proposed for multicomponent droplet generation. The MC-DIP device was designed modularly and could be set up manually without any microfabrication process, exhibiting full accessibility for freshmen after a brief training. This new technique owns advantages in the generation of droplets with predictable sizes and composites. Quantitative experiments of measuring minimum inhibitory concentration (MIC) value via mixing microbes and antibiotics into droplet were conducted to proving its application potential for lab in a drop. Further research on a clinical pathogenic strain revealed that this technique could be potentially applied in the clinical laboratory for antibiotic susceptibility testing.