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.

To reveal the molecular mechanisms of oleaginousness in microalgae, transcriptomic and lipidomic dynamics of the oleaginous microalga Nannochloropsis oceanica IMET1 under nitrogen-replete (N+) and N-depleted (N-) conditions were simultaneously tracked. At the transcript level, enhanced triacylglycerol (TAG) synthesis under N- conditions primarily involved upregulation of seven putative diacylglycerol acyltransferase (DGAT) genes and downregulation of six other DGAT genes, with a simultaneous elevation of the other Kennedy pathway genes. Under N- conditions, despite downregulation of most de novo fatty acid synthesis genes, the pathways that shunt carbon precursors from protein and carbohydrate metabolic pathways into glycerolipid synthesis were stimulated at the transcript level. In particular, the genes involved in supplying carbon precursors and energy for de novo fatty acid synthesis, including those encoding components of the pyruvate dehydrogenase complex (PDHC), glycolysis, and PDHC bypass, and suites of specific transporters, were substantially upregulated under N- conditions, resulting in increased overall TAG production. Moreover, genes involved in the citric acid cycle and β-oxidation in mitochondria were greatly enhanced to utilize the carbon skeletons derived from membrane lipids and proteins to produce additional TAG or its precursors. This temporal and spatial regulation model of oil accumulation in microalgae provides a basis for improving our understanding of TAG synthesis in microalgae and will also enable more rational genetic engineering of TAG production.

The etiology of dental caries remains elusive because of our limited understanding of the complex oral microbiomes. The current methodologies have been limited by insufficient depth and breadth of microbial sampling, paucity of data for diseased hosts particularly at the population level, inconsistency of sampled sites and the inability to distinguish the underlying microbial factors. By cross-validating 16S rRNA gene amplicon-based and whole-genome-based deep-sequencing technologies, we report the most in-depth, comprehensive and collaborated view to date of the adult saliva microbiomes in pilot populations of 19 caries-active and 26 healthy human hosts. We found that: first, saliva microbiomes in human population were featured by a vast phylogenetic diversity yet a minimal organismal core; second, caries microbiomes were significantly more variable in community structure whereas the healthy ones were relatively conserved; third, abundance changes of certain taxa such as overabundance of Prevotella Genus distinguished caries microbiota from healthy ones, and furthermore, caries-active and normal individuals carried different arrays of Prevotella species; and finally, no ‘caries-specific’ operational taxonomic units (OTUs) were detected, yet 147 OTUs were ‘caries associated’, that is, differentially distributed yet present in both healthy and caries-active populations. These findings underscored the necessity of species- and strain-level resolution for caries prognosis, and were consistent with the ecological hypothesis where the shifts in community structure, instead of the presence or absence of particular groups of microbes, underlie the cariogenesis.

Oleaginous microalgae are promising feedstock for biofuels, yet the genetic diversity, origin and evolution of oleaginous traits remain largely unknown. Here we present a detailed phylogenomic analysis of five oleaginous Nannochloropsis species (a total of six strains) and one time-series transcriptome dataset for triacylglycerol (TAG) synthesis on one representative strain. Despite small genome sizes, high coding potential and relative paucity of mobile elements, the genomes feature small cores of ca. 2,700 protein-coding genes and a large pan-genome of >38,000 genes. The six genomes share key oleaginous traits, such as the enrichment of selected lipid biosynthesis genes and certain glycoside hydrolase genes that potentially shift carbon flux from chrysolaminaran to TAG synthesis. The eleven type II diacylglycerol acyltransferase genes (DGAT-2) in every strain, each expressed during TAG synthesis, likely originated from three ancient genomes, including the secondary endosymbiosis host and the engulfed green and red algae. Horizontal gene transfers were inferred in most lipid synthesis nodes with expanded gene doses and many glycoside hydrolase genes. Thus multiple genome pooling and horizontal genetic exchange, together with selective inheritance of lipid synthesis genes and species-specific gene loss, have led to the enormous genetic apparatus for oleaginousness and the wide genomic divergence among present-day Nannochloropsis. These findings have important implications in the screening and genetic engineering of microalgae for biofuels. Microalgae are promising feedstock for biofuels. However, the diversity, origin and evolution of oil-producing microalgal genomes in general, and those of their oleaginous traits in particular, remain poorly understood. We present five new genomes of the oleaginous microalgae Nannochloropsis spp. that allow genus-, species- and strain-level genomic comparison. With each Nannochloropsis genome encoding approximately 6,562–9,915 genes, a core genome of ca. 2,700 genes and a large pan-genome of >38,000 genes were found. The genomes share key genetic features such as gene dose expansion of selected nodes in lipid biosynthesis pathways. Evidence of horizontal gene transfers, primarily from bacteria, was found in most of these nodes. However, the eleven type II acyl-CoA:diacylglycerol acyltransferase genes (DGAT-2),the highest gene dose reported among known organisms, likely originated from three ancient genomes of the secondary endosymbiosis host and the engulfed green and red algae; they were strictly vertically inherited in each of the Nannochloropsis spp. Thus, multiple genome pooling and horizontal genetic exchange have underlain the enormous genetic makeup underlying TAG production in present-day Nannochloropsis.

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 materialPanax ginsengand 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.