Background: Metabolic reconstructions (MRs) are common denominators in systems biology and represent biochemical, genetic, and genomic (BiGG) knowledge-bases for target organisms by capturing currently available information in a consistent, structured manner. Salmonella enterica subspecies I serovar Typhimurium is a human pathogen, causes various diseases and its increasing antibiotic resistance poses a public health problem. Results: Here, we describe a community-driven effort, in which more than 20 experts in S. Typhimurium biology and systems biology collaborated to reconcile and expand the S. Typhimurium BiGG knowledge-base. The consensus MR was obtained starting from two independently developed MRs for S. Typhimurium. Key results of this reconstruction jamboree include i) development and implementation of a community-based workflow for MR annotation and reconciliation; ii) incorporation of thermodynamic information; and iii) use of the consensus MR to identify potential multi-target drug therapy approaches. Conclusion: Taken together, with the growing number of parallel MRs a structured, community-driven approach will be necessary to maximize quality while increasing adoption of MRs in experimental design and interpretation.

There has been a controversy on whether alternatively spliced exons (ASEs) evolve faster than constitutively spliced exons (CSEs). Although it has been noted that ASEs are subject to weaker selective constraints than CSEs, so they evolve faster, there have also been studies that indicated slower evolution in ASEs than in CSEs. In this study, we retrieve more than 5,000 human-mouse orthologous exons and calculate the synonymous (KS) and nonsynonymous (KA) substitution rates in these exons. Our results show that ASEs have higher KA values and higher KA/KS ratios than CSEs, indicating faster amino acid-level evolution in ASEs. The faster evolution may be in part due to weaker selective constraints. It is also possible that the faster rate is in part due to faster functional evolution in ASEs. On the other hand, the majority of ASEs have lower KS values than CSEs. With reference to the substitution rate in introns, we show that the KS values in ASEs are close to the neutral substitution rate, whereas the synonymous substitution rate in CSEs has likely been accelerated. The elevated synonymous rate in CSEs is not related to CpG dinucleotides or low-complexity regions of protein but may be weakly related to codon usage bias. The overall trends of higher KA and lower KS in ASEs than in CSEs are also observed in human-rat and mouse-rat comparisons. Therefore, our observations hold for mammals of different molecular clocks.

DNA cytosine methylation is a central epigenetic marker that is usually mutagenic and may increase the level of sequence divergence. However, methylated genes have been reported to evolve more slowly than unmethylated genes. Hence, there is a controversy on whether DNA methylation is correlated with increased or decreased protein evolutionary rates. We hypothesize that this controversy has resulted from the differential correlations between DNA methylation and the evolutionary rates of coding exons in different genic positions. To test this hypothesis, we compare human–mouse and human–macaque exonic evolutionary rates against experimentally determined single-base resolution DNA methylation data derived from multiple human cell types. We show that DNA methylation is significantly related to within-gene variations in evolutionary rates. First, DNA methylation level is more strongly correlated with C-to-T mutations at CpG dinucleotides in the first coding exons than in the internal and last exons, although it is positively correlated with the synonymous substitution rate in all exon positions. Second, for the first exons, DNA methylation level is negatively correlated with exonic expression level, but positively correlated with both nonsynonymous substitution rate and the sample specificity of DNA methylation level. For the internal and last exons, however, we observe the opposite correlations. Our results imply that DNA methylation level is differentially correlated with the biological (and evolutionary) features of coding exons in different genic positions. The first exons appear more prone to the mutagenic effects, whereas the other exons are more influenced by the regulatory effects of DNA methylation.

Drug-resistant Mycobacterium tuberculosis (MTB), the causative pathogen of tuberculosis (TB), has become a serious threat to global public health. Yet the development of novel drugs against MTB has been lagging. One potentially powerful approach to drug development is computation-aided repositioning of current drugs. However, the effectiveness of this approach has rarely been examined. Here we select the “TB drugome” approach – a protein structure-based method for drug repositioning for tuberculosis treatment – to (1) experimentally validate the efficacy of the identified drug candidates for inhibiting MTB growth, and (2) computationally examine how consistently drug candidates are prioritized, considering changes in input data. Twenty three drugs in the TB drugome were tested. Of them, only two drugs (tamoxifen and 4-hydroxytamoxifen) effectively suppressed MTB growth at relatively high concentrations. Both drugs significantly enhanced the inhibitory effects of three first-line anti-TB drugs (rifampin, isoniazid, and ethambutol). However, tamoxifen is not a top-listed drug in the TB drugome, and 4-hydroxytamoxifen is not approved for use in humans. Computational re-examination of the TB drugome indicated that the rankings were subject to technical and data-related biases. Thus, although our results support the effectiveness of the TB drugome approach for identifying drugs that can potentially be repositioned for stand-alone applications or for combination treatments for TB, the approach requires further refinements via incorporation of additional biological information. Our findings can also be extended to other structure-based drug repositioning methods.

Human-specific small insertions and deletions (HS indels, with lengths <100 bp) are reported to be ubiquitous in the human genome. However, whether these indels contribute to human-specific traits remains unclear. Here we employ a modified McDonald–Kreitman (MK) test and a combinatorial population genetics approach to infer, respectively, the occurrence of positive selection and recent selective sweep events associated with HS indels. We first extract 625,890 HS indels from the human–chimpanzee–macaque–mouse multiple alignments and classify them into nonpolymorphic (41%) and polymorphic (59%) indels with reference to the human indel polymorphism data. The modified MK test is then applied to 100-kb partially overlapped sliding windows across the human genome to scan for the signs of positive selection. After excluding the possibility of biased gene conversion and controlling for false discovery rate, we show that HS indels are potentially positively selected in about 10 Mb of the human genome. Furthermore, the indel-associated positively selected regions overlap with genes more often than expected. However, our result suggests that the potential targets of positive selection are located in noncoding regions. Meanwhile, we also demonstrate that the genomic regions surrounding HS indels are more frequently involved in recent selective sweep than the other regions. In addition, HS indels are associated with distinct recent selective sweep events in different human subpopulations. Our results suggest that HS indels may have been associated with human adaptive changes at both the species level and the subpopulation level.

Organismal complexity is suggested to increase with the complexity of transcriptional and translational regulations. Supporting this notion is a recent study that demonstrated a higher level of tissue-specific gene expression in human than in mouse. However, whether this correlation can be extended beyond mammals remains unclear. In addition, 5' untranslated regions (5'UTRs), which have undergone stochastic elongation during evolution and potentially included an increased number of regulatory elements, may have played an important role in the emergence of organismal complexity. Although the lack of correlation between 5'UTR length and organismal complexity has been proposed, the underlying mechanisms remain unexplored.