细胞外基质蛋白质预测工具研究进展

细胞外基质蛋白质在细胞的一系列生物过程中发挥着重要作用,它的异常调节会导致很多重大疾病。理论细胞外基质蛋白质参考数据是实现细胞外基质蛋白质高效鉴定的基础,研究者们已经基于机器学习的方法开发出一系列的细胞外基质蛋白质预测工具。文中首先阐述了基于机器学习模型构建细胞外基质蛋白质预测工具的基本流程,之后以工具为单位总结了已有细胞外基质蛋白质预测工具的研究成果,最后提出了细胞外基质蛋白质预测工具目前面临的问题和可能的优化方法。     

Cross-species enhancer prediction using machine learning

Cis-regulatory elements (CREs) are non-coding parts of the genome that play a critical role in gene expression regulation. Enhancers, as an important example of CREs, interact with genes to influence complex traits like disease, heat tolerance and growth rate. Much of what is known about enhancers come from studies of humans and a few model organisms like mouse, with little known about other mammalian species. Previous studies have attempted to identify enhancers in less studied mammals using comparative genomics but with limited success. Recently, Machine Learning (ML) techniques have shown promising results to predict enhancer regions. Here, we investigated the ability of ML methods to identify enhancers in three non-model mammalian species (cattle, pig and dog) using human and mouse enhancer data from VISTA and publicly available ChIP-seq. We tested nine models, using four different representations of the DNA sequences in cross-species prediction using both the VISTA dataset and species-specific ChIP-seq data. We identified between 809,399 and 877,278 enhancer-like regions (ELRs) in the study species (11.6–13.7% of each genome). These predictions were close to the ~8% proportion of ELRs that covered the human genome. We propose that our ML methods have predictive ability for identifying enhancers in non-model mammalian species. We have provided a list of high confidence enhancers at https://github.com/DaviesCentreInformatics/Cross-species-enhancer-prediction and believe these enhancers will be of great use to the community.     

Genome-Wide Prediction and Validation of Intergenic Enhancers in Arabidopsis Using Open Chromatin Signatures

Enhancers are important regulators of gene expression in eukaryotes. Enhancers function independently of their distance and orientation to the promoters of target genes. Thus, enhancers have been difficult to identify. Only a few enhancers, especially distant intergenic enhancers, have been identified in plants. We developed an enhancer prediction system based exclusively on the DNase I hypersensitive sites (DHSs) in the Arabidopsis thaliana genome. A set of 10,044 DHSs located in intergenic regions, which are away from any gene promoters, were predicted to be putative enhancers. We examined the functions of 14 predicted enhancers using the β-glucuronidase gene reporter. Ten of the 14 (71%) candidates were validated by the reporter assay. We also designed 10 constructs using intergenic sequences that are not associated with DHSs, and none of these constructs showed enhancer activities in reporter assays. In addition, the tissue specificity of the putative enhancers can be precisely predicted based on DNase I hypersensitivity data sets developed from different plant tissues. These results suggest that the open chromatin signature-based enhancer prediction system developed in Arabidopsis may serve as a universal system for enhancer identification in plants.     

The chromatin fingerprint of gene enhancer elements

Different cell types within a single organism are generally distinguished by strikingly different patterns of gene expression, which are dynamic throughout development and adult life. Distal enhancer elements are key drivers of spatiotemporal specificity in gene regulation. Often located tens of kilobases from their target promoters and functioning in an orientation-independent manner, the identification of bona fide enhancers has proved a formidable challenge. With the development of ChIP-seq, global cataloging of putative enhancers has become feasible. Here, we review the current understanding of the chromatin landscape at enhancers and how these chromatin features enable robust identification of tissue-specific enhancers.     

Evolutionary origin of the Otx2 enhancer for its expression in visceral endoderm

In the mouse, the Otx2 gene has been shown to play essential roles in the visceral endoderm during anterior-posterior axis formation and head induction. While these are primary processes in vertebrate embryogenesis, the visceral endoderm is a tissue unique to mammals. Two enhancers (VE and CM) have been previously found to direct Otx2 expression during early embryogenesis. This study demonstrates that in anterior visceral endoderm the CM enhancer does not have an activity by itself, but enhances the activity of the VE enhancer. These two enhancers also cooperate for the activities in anterior mesendoderm and cephalic mesenchyme. Comparative studies suggest that VE enhancer function was most likely established before the divergence of sarcopterygians into Actinistia, Dipnoi and tetrapods, while the nucleotide sequence corresponding to the VE enhancer was already present in the last common ancestor of bony fishes. The CM enhancer sequence and function would have been also established in ancestral sarcopterygians. The VE/CM enhancers and their gene cascades in the ancestral sarcopterygian head organizer would then have been co-opted by amphibian deep endoderm cells and mammalian visceral endoderm cells for the head development.     

A regulatory code for neurogenic gene expression in the Drosophila embryo

Bioinformatics methods have identified enhancers that mediate restricted expression in the Drosophila embryo. However, only a small fraction of the predicted enhancers actually work when tested in vivo. In the present study, co-regulated neurogenic enhancers that are activated by intermediate levels of the Dorsal regulatory gradient are shown to contain several shared sequence motifs. These motifs permitted the identification of new neurogenic enhancers with high precision: five out of seven predicted enhancers direct restricted expression within ventral regions of the neurogenic ectoderm. Mutations in some of the shared motifs disrupt enhancer function, and evidence is presented that the Twist and Su(H) regulatory proteins are essential for the specification of the ventral neurogenic ectoderm prior to gastrulation. The regulatory model of neurogenic gene expression defined in this study permitted the identification of a neurogenic enhancer in the distant Anopheles genome. We discuss the prospects for deciphering regulatory codes that link primary DNA sequence information with predicted patterns of gene expression.     

Requirements and reliability of AI in the medical context

The digital information age has been a catalyst in creating a renewed interest in Artificial Intelligence (AI) approaches, especially the subclass of computer algorithms that are popularly grouped into Machine Learning (ML). These methods have allowed one to go beyond limited human cognitive ability into understanding the complexity in the high dimensional data. Medical sciences have seen a steady use of these methods but have been slow in adoption to improve patient care. There are some significant impediments that have diluted this effort, which include availability of curated diverse data sets for model building, reliable human-level interpretation of these models, and reliable reproducibility of these methods for routine clinical use. Each of these aspects has several limiting conditions that need to be balanced out, considering the data/model building efforts, clinical implementation, integration cost to translational effort with minimal patient level harm, which may directly impact future clinical adoption. In this review paper, we will assess each aspect of the problem in the context of reliable use of the ML methods in oncology, as a representative study case, with the goal to safeguard utility and improve patient care in medicine in general.     

Computational tools for exploring sequence databases as a resource for antimicrobial peptides

Data mining has been recognized by many researchers as a hot topic in different areas. In the post-genomic era, the growing number of sequences deposited in databases has been the reason why these databases have become a resource for novel biological information. In recent years, the identification of antimicrobial peptides (AMPs) in databases has gained attention. The identification of unannotated AMPs has shed some light on the distribution and evolution of AMPs and, in some cases, indicated suitable candidates for developing novel antimicrobial agents. The data mining process has been performed mainly by local alignments and/or regular expressions. Nevertheless, for the identification of distant homologous sequences, other techniques such as antimicrobial activity prediction and molecular modelling are required. In this context, this review addresses the tools and techniques, and also their limitations, for mining AMPs from databases. These methods could be helpful not only for the development of novel AMPs, but also for other kinds of proteins, at a higher level of structural genomics. Moreover, solving the problem of unannotated proteins could bring immeasurable benefits to society, especially in the case of AMPs, which could be helpful for developing novel antimicrobial agents and combating resistant bacteria.     

Sequence elements essential for function of the Xenopus laevis ribosomal DNA enhancers.

The intergenic spacer region of the Xenopus laevis ribosomal DNA contains multiple elements which are either 60 or 81 base pairs long. Clusters of these elements have previously been shown to act as position- and distance-independent enhancers on an RNA polymerase I promoter when located in cis. By a combination of deletion and linker scanner mutagenesis we show that the sequences essential for enhancer function are located within a 56-base-pair region that is present in both the 60- and 81-base-pair repeats. Within the 56-base-pair region one linker scanner mutation was found to be relatively neutral, suggesting that each enhancer element may be composed of two smaller domains. Each 56-base-pair region appears to be an independent enhancer with multiple enhancers being additive in effect. We review the current evidence concerning the mechanism of action of these enhancers.