Assessment and characterization of gut microbiota has become a major research area in human disease, including type 2 diabetes, the most prevalent endocrine disease worldwide. To carry out analysis on gut microbial content in patients with type 2 diabetes, we developed a protocol for a metagenome-wide association study (MGWAS) and undertook a two-stage MGWAS based on deep shotgun sequencing of the gut microbial DNA from 345 Chinese individuals. We identified and validated approximately 60,000 type-2-diabetes-associated markers and established the concept of a metagenomic linkage group, enabling taxonomic species-level analyses. MGWAS analysis showed that patients with type 2 diabetes were characterized by a moderate degree of gut microbial dysbiosis, a decrease in the abundance of some universal butyrate-producing bacteria and an increase in various opportunistic pathogens, as well as an enrichment of other microbial functions conferring sulphate reduction and oxidative stress resistance. An analysis of 23 additional individuals demonstrated that these gut microbial markers might be useful for classifying type 2 diabetes.

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Coronavirus disease 2019 (COVID-19), the global pandemic caused by SARS-CoV-2, has resulted thus far in greater than 933,000 deaths worldwide; yet disease pathogenesis remains unclear. Clinical and immunological features of patients with COVID-19 have highlighted a potential role for changes in immune activity in regulating disease severity. However, little is known about the responses in human lung tissue, the primary site of infection. Here we show that pathways related to neutrophil activation and pulmonary fibrosis are among the major up-regulated transcriptional signatures in lung tissue obtained from patients who died of COVID-19 in Wuhan, China. Strikingly, the viral burden was low in all samples, which suggests that the patient deaths may be related to the host response rather than an active fulminant infection. Examination of the colonic transcriptome of these patients suggested that SARS-CoV-2 impacted host responses even at a site with no obvious pathogenesis. Further proteomics analysis validated our transcriptome findings and identified several key proteins, such as the SARS-CoV-2 entry-associated protease cathepsins B and L and the inflammatory response modulator S100A8/A9, that are highly expressed in fatal cases, revealing potential drug targets for COVID-19.

BackgroundMetagenomic next-generation sequencing (mNGS) is a powerful method for pathogen detection. In this study, we assessed the value of mNGS for bronchoalveolar lavage (BAL) samples in the diagnosis of pulmonary infections.MethodsFrom February 2018 to April 2019, BAL samples were collected from 235 patients with suspected pulmonary infections. mNGS and microbial culture were performed to evaluate the effectiveness of mNGS in pulmonary infection diagnosis.ResultsWe employed mNGS to evaluate the alpha diversity, results suggesting that patients with confirmed pathogens had a lower microbial diversity index compared to that of patients with uncertain pathogens. For the patients admitted to the respiratory intensive care unit (RICU) or on a ventilator, they experienced a lower diversity index than that of the patients in the general ward or not on a ventilator. In addition, mNGS of BAL had a diagnostic sensitivity of 88.89% and a specificity of 14.86% in pulmonary infection, with 21.16% positive predictive value (PPV) and 83.87% negative predictive value (NPV). When rare pathogens were excluded, the sensitivity of mNGS decreased to 73.33%, and the specificity increased to 41.71%. For patients in the simple pulmonary infection group and the immunocompromised group, the main infection types were bacterial infection (58.33%) and mixed-infection (43.18%). Furthermore, mNGS had an advantage over culture in describing polymicrobial ecosystem, demonstrating the microbial distribution and the dominant strains of the respiratory tract in patients with different underlying diseases.ConclusionsThe study indicated that mNGS of BAL samples could provide more accurate diagnostic information in pulmonary infections and demonstrate the changes of respiratory microbiome in different underlying diseases. This method might play an important role in the clinical use of antimicrobial agents in the future.

Cold stress limits plant geographical distribution and influences plant growth, development, and yields. Plants as sessile organisms have evolved complex biochemical and physiological mechanisms to adapt to cold stress. These mechanisms are regulated by a series of transcription factors and proteins for efficient cold stress acclimation. It has been established that the ICE-CBF-COR signaling pathway in plants regulates how plants acclimatize to cold stress. Cold stress is perceived by receptor proteins, triggering signal transduction, and Inducer of CBF Expression (ICE) genes are activated and regulated, consequently upregulating the transcription and expression of the C-repeat Binding Factor (CBF) genes. The CBF protein binds to the C-repeat/Dehydration Responsive Element (CRT/DRE), a homeopathic element of the Cold Regulated genes (COR gene) promoter, activating their transcription. Transcriptional regulations and post-translational modifications regulate and modify these entities at different response levels by altering their expression or activities in the signaling cascade. These activities then lead to efficient cold stress tolerance. This paper contains a concise summary of the ICE-CBF-COR pathway elucidating on the cross interconnections with other repressors, inhibitors, and activators to induce cold stress acclimation in plants.

Viral infections can alter host transcriptomes by manipulating host splicing machinery. Despite intensive transcriptomic studies on SARS-CoV-2, a systematic analysis of alternative splicing (AS) in severe COVID-19 patients remains largely elusive. Here we integrated proteomic and transcriptomic sequencing data to study AS changes in COVID-19 patients. We discovered that RNA splicing is among the major down-regulated proteomic signatures in COVID-19 patients. The transcriptome analysis showed that SARS-CoV-2 infection induces widespread dysregulation of transcript usage and expression, affecting blood coagulation, neutrophil activation, and cytokine production. Notably, CD74 and LRRFIP1 had increased skipping of an exon in COVID-19 patients that disrupts a functional domain, which correlated with reduced antiviral immunity. Furthermore, the dysregulation of transcripts was strongly correlated with clinical severity of COVID-19, and splice-variants may contribute to unexpected therapeutic activity. In summary, our data highlight that a better understanding of the AS landscape may aid in COVID-19 diagnosis and therapy.

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Background Listeria monocytogenes (L. monocytogenes) is a facultative intracellular bacterial pathogen which can invade different mammalian cells and reach to the central nervous system (CNS), leading to meningoencephalitis and brain abscesses. In the diagnosis of L. monocytogenes meningoencephalitis (LMM), the traditional test often reports negative owing to the antibiotic treatment or a low number of bacteria in the cerebrospinal fluid. To date, timely diagnosis and accurate treatment remains a challenge for patients with listeria infections. Case presentation We present the case of a 66-year-old woman whose clinical manifestations were suspected as tuberculous meningoencephalitis, but the case was finally properly diagnosed as LMM by next-generation sequencing (NGS). The patient was successfully treated using a combined antibacterial therapy, comprising ampicillin and trimethoprim-sulfamethoxazole. Conclusion To improve the sensitivity of LMM diagnosis, we used NGS for the detection of L. monocytogenes. Hence, the clinical utility of this approach can be very helpful since it provides quickly and trust results.