The industrial yeast Saccharomyces cerevisiae is a traditional ethanologenic agent and a promising biocatalyst for advanced biofuels production using lignocellulose materials. Here we present the genomic background of type strain NRRL Y-12632 and its transcriptomic response to 5-hydroxymethyl-2-furaldehyde (HMF), a commonly encountered toxic compound liberated from lignocellulosic-biomass pretreatment, in dissecting the genomic mechanisms of yeast tolerance. Compared with the genome of laboratory model strain S288C, we identified more than 32,000 SNPs in Y-12632 with 23,000 missense and nonsense SNPs. Enriched sequence mutations occurred for genes involved in MAPK- and phosphatidylinositol (PI)- signaling pathways in strain Y-12632, with 41 and 13 genes containing non-synonymous SNPs, respectively. Many of these mutated genes displayed consistent up-regulated signature expressions in response to challenges of 30 mM HMF. Analogous single-gene deletion mutations of these genes showed significantly sensitive growth response on a synthetic medium containing 20 mM HMF. Our results suggest at least three MAPK-signaling pathways, especially for the cell-wall integrity pathway, and PI-signaling pathways to be involved in mediation of yeast tolerance against HMF in industrial yeast Saccharomyces cerevisiae. Higher levels of sequence variations were also observed for genes involved in purine and pyrimidine metabolism pathways.

The metagenomic method directly sequences and analyses genome information from microbial communities. The main computational tasks for metagenomic analyses include taxonomical and functional structure analysis for all genomes in a microbial community (also referred to as a metagenomic sample). With the advancement of Next Generation Sequencing (NGS) techniques, the number of metagenomic samples and the data size for each sample are increasing rapidly. Current metagenomic analysis is both data- and computation- intensive, especially when there are many species in a metagenomic sample, and each has a large number of sequences. As such, metagenomic analyses require extensive computational power. The increasing analytical requirements further augment the challenges for computation analysis. In this work, we have proposed Parallel-META 2.0, a metagenomic analysis software package, to cope with such needs for efficient and fast analyses of taxonomical and functional structures for microbial communities. Parallel-META 2.0 is an extended and improved version of Parallel-META 1.0, which enhances the taxonomical analysis using multiple databases, improves computation efficiency by optimized parallel computing, and supports interactive visualization of results in multiple views. Furthermore, it enables functional analysis for metagenomic samples including short-reads assembly, gene prediction and functional annotation. Therefore, it could provide accurate taxonomical and functional analyses of the metagenomic samples in high-throughput manner and on large scale.

The NGS (next generation sequencing)-based metagenomic data analysis is becoming the mainstream for the study of microbial communities. Faced with a large amount of data in metagenomic research, effective data visualization is important for scientists to effectively explore, interpret and manipulate such rich information. The visualization of the metagenomic data, especially multi-sample data, is one of the most critical challenges. The different data sample sources, sequencing approaches and heterogeneous data formats make robust and seamless data visualization difficult. Moreover, researchers have different focuses on metagenomic studies: taxonomical or functional, sample-centric or genome-centric, single sample or multiple samples, etc. However, current efforts in metagenomic data visualization cannot fulfill all of these needs, and it is extremely hard to organize all of these visualization effects in a systematic manner. An extendable, interactive visualization tool would be the method of choice to fulfill all of these visualization needs. In this paper, we have present MetaSee, an extendable toolbox that facilitates the interactive visualization of metagenomic samples of interests. The main components of MetaSee include: (I) a core visualization engine that is composed of different views for comparison of multiple samples: Global view, Phylogenetic view, Sample view and Taxa view, as well as link-out for more in-depth analysis; (II) front-end user interface with real metagenomic models that connect to the above core visualization engine and (III) open-source portal for the development of plug-ins for MetaSee. This integrative visualization tool not only provides the visualization effects, but also enables researchers to perform in-depth analysis of the metagenomic samples of interests. Moreover, its open-source portal allows for the design of plug-ins for MetaSee, which would facilitate the development of any additional visualization effects.

Metagenomics method directly sequences and analyses genome information from microbial communities. There are usually more than hundreds of genomes from different microbial species in the same community, and the main computational tasks for metagenomic data analyses include taxonomical and functional component examination of all genomes in the microbial community. Metagenomic data analysis is both data- and computation- intensive, which requires extensive computational power. Most of the current metagenomic data analysis softwares were designed to be used on a single computer or single computer clusters, which could not match with the fast increasing number of large metagenomic projects' computational requirements. Therefore, advanced computational methods and pipelines have to be developed to cope with such need for efficient analyses.

Human saliva microbiota is phylogenetically divergent among host individuals yet their roles in health and disease are poorly appreciated. We employed a microbial functional gene microarray, HuMiChip 1.0, to reconstruct the global functional profiles of human saliva microbiota from ten healthy and ten caries-active adults. Saliva microbiota in the pilot population featured a vast diversity of functional genes. No significant distinction in gene number or diversity indices was observed between healthy and caries-active microbiota. However, co-presence network analysis of functional genes revealed that caries-active microbiota was more divergent in non-core genes than healthy microbiota, despite both groups exhibited a similar degree of conservation at their respective core genes. Furthermore, functional gene structure of saliva microbiota could potentially distinguish caries-active patients from healthy hosts. Microbial functions such as Diaminopimelate epimerase, Prephenate dehydrogenase, Pyruvate-formate lyase and N-acetylmuramoyl-L-alanine amidase were significantly linked to caries. Therefore, saliva microbiota carried disease-associated functional signatures, which could be potentially exploited for caries diagnosis.

The phytohormone auxin is essential for plant growth and development, and YUCCA (YUC) proteins catalyze a rate-limiting step for endogenous auxin biosynthesis. Despite YUC family genes have been isolated from several species, systematic expression analyses of YUCs in response to abiotic stress are lacking, and little is known about the function of YUC homologs in agricultural crops. Cucumber (Cucumis sativus L.) is a world cultivated vegetable crop with great economical and nutritional value. In this study, we isolated 10 YUC family genes (CsYUCs) from cucumber and explored their expression pattern under four types of stress treatments. Our data showed that CsYUC8 and CsYUC9 were specifically upregulated to elevate the auxin level under high temperature. CsYUC10b was dramatically increased but CsYUC4 was repressed in response to low temperature. CsYUC10a and CsYUC11 act against the upregulation of CsYUC10b under salinity stress, suggesting that distinct YUC members participate in different stress response, and may even antagonize each other to maintain the proper auxin levels in cucumber. Further, CsYUC11 was specifically expressed in the male flower in cucumber, and enhanced tolerance to salinity stress and regulated pedicel and stamen development through auxin biosynthesis in Arabidopsis.

Findings on the relationship between total bilirubin level (TBL) and diabetic retinopathy (DR) are inconsistent. Thus, we carried out a meta-analysis to investigate the relationship between TBL and the risk of DR.

Studying the large-scale protein-protein interaction (PPI) network is important in understanding biological processes. The current research presents the first PPI map of swine, which aims to give new insights into understanding their biological processes.

With the advancement of systems biology research, we have already seen great progress in pharmacology studies, especially in network pharmacology. Network pharmacology has been proven to be effective for establishing the "compounds-proteins/genes-diseases" network, and revealing the regulation principles of small molecules in a high-throughput manner, thus would be very effective for the analysis of drug combinations, especially for TCM preparations. In this work, we have proposed the TCM-Mesh system, which records TCM-related information collected from various resources and could serve for network pharmacology analysis for TCM preparations in a high-throughput manner (http://mesh.tcm.microbioinformatics.org/). Currently, the database contains 6,235 herbs, 383,840 compounds, 14,298 genes, 6,204 diseases, 144,723 gene-disease associations, 3,440,231 pairs of gene interactions, 163,221 side effect records and 71 toxic records, and web-based software construct a network between herbs and treated diseases, which will help to understand the underlying mechanisms for TCM preparations at molecular levels. We have used 1,293 FDA-approved drugs, as well as compounds from an herbal material Panax ginseng and a patented drug Liuwei Dihuang Wan (LDW) for evaluating our database. By comparison of different databases, as well as checking against literature, we have demonstrated the completeness, effectiveness, and accuracy of our database.

Agricultural activities, including stock-farming, planting industry, and fish aquaculture, can affect the physicochemical and biological characters of freshwater lakes. However, the effects of pollution producing by agricultural activities on microbial ecosystem of lakes remain unclear. Hence, in this work, we selected Honghu Lake as a typical lake that is influenced by agriculture activities. We collected water and sediment samples from 18 sites, which span a wide range of areas from impacted and less-impacted areas. We performed a geospatial analysis on the composition of microbial communities associated with physicochemical properties and antibiotic pollution of samples. The co-occurrence networks of water and sediment were also built and analyzed. Our results showed that the microbial communities of impacted and less-impacted samples of water were largely driven by the concentrations of TN, TP, NO3--N, and NO2--N, while those of sediment were affected by the concentrations of Sed-OM and Sed-TN. Antibiotics have also played important roles in shaping these microbial communities: the concentrations of oxytetracycline and tetracycline clearly reflected the variance in taxonomic diversity and predicted functional diversity between impacted and less-impacted sites in water and sediment samples, respectively. Furthermore, for samples from both water and sediment, large differences of network topology structures between impacted and less-impacted were also observed. Our results provide compelling evidence that the microbial community can be used as a sentinel of eutrophication and antibiotics pollution risk associated with agricultural activity; and that proper monitoring of this environment is vital to maintain a sustainable environment in Honghu Lake.

The research field of systems biology has greatly advanced and, as a result, the concept of network pharmacology has been developed. This advancement, in turn, has shifted the paradigm from a "one-target, one-drug" mode to a "network-target, multiple-component-therapeutics" mode. Network pharmacology is more effective for establishing a "compound-protein/gene-disease" network and revealing the regulation principles of small molecules in a high-throughput manner. This approach makes it very powerful for the analysis of drug combinations, especially Traditional Chinese Medicine (TCM) preparations. In this work, we first summarized the databases and tools currently used for TCM research. Second, we focused on several representative applications of network pharmacology for TCM research, including studies on TCM compatibility, TCM target prediction, and TCM network toxicology research. Third, we compared the general statistics of several current TCM databases and evaluated and compared the search results of these databases based on 10 famous herbs. In summary, network pharmacology is a rational approach for TCM studies, and with the development of TCM research, powerful and comprehensive TCM databases have emerged but need further improvements. Additionally, given that several diseases could be treated by TCMs, with the mediation of gut microbiota, future studies should focus on both the microbiome and TCMs to better understand and treat microbiome-related diseases.

The single-cell analysis is becoming a powerful method for early detection of the abnormal variant in tissues, especially for profiling a small number of heterogeneous cells. With the advancement of sequencing technologies, many types of non-coding elements including miRNAs and lncRNAs which shed light on their heterogeneous patterns and functions among cells, have been profiled at the single-cell level. However, the complete picture of circRNA profile at single-cell level is still lacking. In this study, RNA-Seq data obtained from single HEK293T cells have been used to analyze expressions and functions of heterogeneous circRNA profiles. The enrichment patterns of circRNAs, interactions with miRNAs and pathways such as ErbB signaling pathway and protein processing in endoplasmic reticulum, have also been investigated. The results showed that circRNAs had a specific distribution pattern which was implicated with expression, miRNA and functional profiles at single-cell level. This assessment study of the expressions and functions of circRNAs at single-cell level shed light on heterogeneities among single cells.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) replicates throughout human airways. The polarized human airway epithelium (HAE) cultured at an airway-liquid interface (HAE-ALI) is an in vitro model mimicking the in vivo human mucociliary airway epithelium and supports the replication of SARS-CoV-2. Prior studies characterized only short-period SARS-CoV-2 infection in HAE. In this study, continuously monitoring the SARS-CoV-2 infection in HAE-ALI cultures for a long period of up to 51 days revealed that SARS-CoV-2 infection was long lasting with recurrent replication peaks appearing between an interval of approximately 7 to 10 days, which was consistent in all the tested HAE-ALI cultures derived from 4 lung bronchi of independent donors. We also identified that SARS-CoV-2 does not infect HAE from the basolateral side, and the dominant SARS-CoV-2 permissive epithelial cells are ciliated cells and goblet cells, whereas virus replication in basal cells and club cells was not detected. Notably, virus infection immediately damaged the HAE, which is demonstrated by dispersed zonula occludens-1 (ZO-1) expression without clear tight junctions and partial loss of cilia. Importantly, we identified that SARS-CoV-2 productive infection of HAE requires a high viral load of >2.5 × 105 virions per cm2 of epithelium. Thus, our studies highlight the importance of a high viral load and that epithelial renewal initiates and maintains a recurrent infection of HAE with SARS-CoV-2.IMPORTANCE The pandemic of coronavirus disease 2019 (COVID-19), which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has led to >35 million confirmed cases and >1 million fatalities worldwide. SARS-CoV-2 mainly replicates in human airway epithelia in COVID-19 patients. In this study, we used in vitro cultures of polarized human bronchial airway epithelium to model SARS-CoV-2 replication for a period of 21 to 51 days. We discovered that in vitro airway epithelial cultures endure a long-lasting SARS-CoV-2 propagation with recurrent peaks of progeny virus release at an interval of approximately 7 to 10 days. Our study also revealed that SARS-CoV-2 infection causes airway epithelia damage with disruption of tight junction function and loss of cilia. Importantly, SARS-CoV-2 exhibits a polarity of infection in airway epithelium only from the apical membrane; it infects ciliated and goblet cells but not basal and club cells. Furthermore, the productive infection of SARS-CoV-2 requires a high viral load of over 2.5 × 105 virions per cm2 of epithelium. Our study highlights that the proliferation of airway basal cells and regeneration of airway epithelium may contribute to the recurrent infections.

The ocean microbiome represents one of the largest microbiomes and produces nearly half of the primary energy on the planet through photosynthesis or chemosynthesis. Using recent advances in marine genomics, we explore new applications of oceanic metagenomes for protein structure and function prediction.

Shewanella strains are important dissimilatory metal-reducing bacteria which are widely distributed in diverse habitats. Despite efforts to genomically characterize Shewanella, knowledge of the molecular components, functional information and evolutionary patterns remain lacking, especially for their compatibility in the metal-reducing pathway. The increasing number of genome sequences of Shewanella strains offers a basis for pan-genome studies.

The gut microbiota of intensive care unit (ICU) patients displays extreme dysbiosis associated with increased susceptibility to organ failure, sepsis, and septic shock. However, such dysbiosis is difficult to characterize owing to the high dimensional complexity of the gut microbiota. We tested whether the concept of enterotype can be applied to the gut microbiota of ICU patients to describe the dysbiosis. We collected 131 fecal samples from 64 ICU patients diagnosed with sepsis or septic shock and performed 16S rRNA gene sequencing to dissect their gut microbiota compositions. During the development of sepsis or septic shock and during various medical treatments, the ICU patients always exhibited two dysbiotic microbiota patterns, or ICU-enterotypes, which could not be explained by host properties such as age, sex, and body mass index, or external stressors such as infection site and antibiotic use. ICU-enterotype I (ICU E1) comprised predominantly Bacteroides and an unclassified genus of Enterobacteriaceae, while ICU-enterotype II (ICU E2) comprised predominantly Enterococcus. Among more critically ill patients with Acute Physiology and Chronic Health Evaluation II (APACHE II) scores > 18, septic shock was more likely to occur with ICU E1 (P = 0.041). Additionally, ICU E1 was correlated with high serum lactate levels (P = 0.007). Therefore, different patterns of dysbiosis were correlated with different clinical outcomes, suggesting that ICU-enterotypes should be diagnosed as independent clinical indices. Thus, the microbial-based human index classifier we propose is precise and effective for timely monitoring of ICU-enterotypes of individual patients. This work is a first step toward precision medicine for septic patients based on their gut microbiota profiles.

Glycyrrhiza uralensis Fisch. is an important, perennial medicinal plant whose root microbiome is considered to play an important role in promoting accumulation of effective medicinal ingredients (liquiritin and glycrrhizic acid). Here, we report a comprehensive analysis of the microbial community structural composition and metabolite-plant-microbes association of G. uralensis Fisch. We collected both soil and rhizosphere samples of G. uralensis from different environmental conditions (cultivated and wild) and growth years (grown for one year and three years). Our data revealed higher species diversity in the wild group than in the cultivated group. The core rhizosphere microbiome of G. uralensis comprised 78 genera, including Bacillus, Pseudomonas, Rhizobium, some of which were potential plant beneficial microbes. Our results suggest that the growth of G. uralensis has a correlation with the root-associated microbiota assemblage. Integrated analysis among rhizosphere microbial taxa, plant gene expressions, and liquiritin and glycrrhizic acid accumulation showed that the liquiritin and glycrrhizic acid accumulation exhibited associations with the rhizosphere microbial composition at the genus level. The results provide valuable information to guide cultivation of G. uralensis, and potentially to harness the power of the root-associated microbiota to improve medicinal plant production.

Gut microbial dysbiosis has been associated with hypertension. An extremely high incidence of essential hypertension was found in the Han and the Yugur people who resided in Sunan County in China's nomadic steppes, with little population movement. To investigate gut microbial contributions to this high incidence of hypertension, we recruited a total of 1, 242 Yugur and Han people, who had resided in Sunan County for more than 15 years and accounted for 3% of the local population. The epidemiological survey of 1,089 individuals indicated their nearly 1.8-times-higher prevalence of hypertension (38.2 to 43.3%) than the average in China (23.2%), under a special high-calorie diet based on wheat, cattle, mutton, and animal offal. Investigations of the fecal microbiota of another cohort of 153 individuals revealed that certain Lachnospiraceae genera were positively correlated with high-density lipoprotein cholesterol (HDL-C) but negatively correlated with systolic blood pressure (SBP) and diastolic blood pressure (DBP). HDL-C was negatively correlated with SBP and DBP. We further observed that the serum butyrate content was lower in both Han and Yugur people with hypertension than in those without hypertension. This study gives novel insight into the role of gut microbial dysbiosis in hypertension modulation under a high-calorie diet, where the notable depletion of Lachnospiraceae genera might lead to less production of butyrate, contributing to the lower level of HDL-C and elevating blood pressure in hypertension. IMPORTANCE Dietary nutrients can be converted by the gut microbiota into metabolites such as short-chain fatty acids, which may serve as disease-preventing agents in hypertension. Due to the limited population mobility and unique high-calorie dietary habits, the cohort of this study can serve as a representative cohort for elucidating the associations between the gut microbiota and hypertension under a high-calorie diet. Moreover, low levels of HDL-C have previously been associated with an increased risk of various cardiovascular diseases (CVDs). Our findings provide new insight showing that low levels of HDL-C may be a potential medium between the depletion of Lachnospiraceae genera and hypertension under a high-calorie diet, which might also be a potential candidate for other CVDs.

Thyroid cancer (TC) is the most common endocrine tumor, amongst which anaplastic thyroid carcinoma (ATC) is the most deadly. Aurora-A usually functions as oncogenes, and its inhibitor Alisertib exerts a powerful antitumor effect in various tumors. However, the mechanism of Aurora-A in regulating TC cell energy supply remains unclear. In the present study, we demonstrated the antitumor effect of Alisertib and an association between high Aurora-A expression and shorter survival. Multi-omics data and in vitro validation data suggested that Aurora-A induced PFKFB3-mediated glycolysis to increase ATP supply, which significantly upregulated the phosphorylation of ERK and AKT. Furthermore, the combination of Alisertib and Sorafenib had a synergistic effect, further confirmed in xenograft models and in vitro. Collectively, our study provides compelling evidence of the prognostic value of Aurora-A expression and suggests that Aurora-A upregulates PFKFB3-mediated glycolysis to enhance ATP supply and promote TC progression. Combining Alisertib with Sorafenib has huge prospects for application in treating advanced thyroid carcinoma.

Leaf rust, caused by Puccinia triticina Eriksson (Pt), is one of the most severe foliar diseases of wheat. Breeding for leaf rust resistance is a practical and sustainable method to control this devastating disease. Here, we report the identification of Lr47, a broadly effective leaf rust resistance gene introgressed into wheat from Aegilops speltoides. Lr47 encodes a coiled-coil nucleotide-binding leucine-rich repeat protein that is both necessary and sufficient to confer Pt resistance, as demonstrated by loss-of-function mutations and transgenic complementation. Lr47 introgression lines with no or reduced linkage drag are generated using the Pairing homoeologous1 mutation, and a diagnostic molecular marker for Lr47 is developed. The coiled-coil domain of the Lr47 protein is unable to induce cell death, nor does it have self-protein interaction. The cloning of Lr47 expands the number of leaf rust resistance genes that can be incorporated into multigene transgenic cassettes to control this devastating disease.