In recent years, adaptive laboratory evolution (ALE) has emerged as a powerful tool for basic research in microbiology (e.g., molecular mechanisms of microbial evolution) and efforts on evolutionary engineering of microbial strains (e.g., accelerated evolution of industrial strains by bringing beneficial mutations). The ongoing rapid development of next-generation sequencing platforms has provided novel insights into growth kinetics and metabolism of microbes, and thus led to great advances of this technique. In this review, we summarize recent advances in the applications of long-term and short-term ALE techniques mainly for microbial strain engineering, and different modes of ALE are also introduced. Furthermore, we discuss the current limitations of ALE and potential solutions. We believe that the information reviewed here will make a significant contribution to further advancement of ALE.
High-Throughput Nucleotide Sequencing ; Laboratories ; Mutation

Objective: To evaluate the impact of the targeted next-generation sequencing (NGS) assay for difficult congenital anemias. Methods: Blood Disease Hospital Anemia Panel 2014 (BDHAP-2014) including 217 known genes of congenital anemias was developed. NGS and parental verification were performed for patients who were suspected diagnosed with congenital anaemia from August 2014 to July 2017. Results: A total of 46 patients were enrolled in this study, the clinical suspection were 11 cases Fanconi anemia (FA), 8 cases congenital dyserythropoietic anemia (CDA), 6 cases congenital sideroblast anemia (CSA), 12 cases congenital hemolytic anemia (CHA), 1 case dyskeratosis congenital (DC), 4 cases iron-refractory iron deficiency anemia and 4 cases unexplained cytopenia (Uc), respectively. 28 (60.9%) of 46 patients became confirmed cases after targeted NGS, corresponding to 44 mutations of which 33 were new. 26(56.5%) patients with results of the assay matching to clinical suspection, including FA (5/11, 45.5%), CSA (6/6, 100.0%), CDA (3/8, 37.5%) and CHA (12/12, 100.0%). 2 (4.3%) cases not matching to clinical suspection, including dyskeratosis congenital (DC) was made in 1(2.2%) patients with suspected FA and familial hemophagocytic lymphohistiocytosis (FHL) was made in 1(2.2%) patients with suspected unexplained cytopenia (Uc). In 12 CHA patients, the hemolytic type was further clarified by the NGS. The remaining 18 cases were not clearly diagnosed. Conclusion: Targeted NGS assay is of major impact on congenital anemias. The assay should be used routinely in congenital anemias.
Anemia ; High-Throughput Nucleotide Sequencing ; Humans

The development of high-throughput sequencing techniques enabled a deeper and more comprehensive understanding of environmental microbiology. Specifically, the third-generation sequencing techniques represented by nanopore sequencing have greatly promoted the development of environmental microbiology research due to its advantages such as long sequencing reads, fast sequencing speed, real-time monitoring of sequencing data, and convenient machine carrying, as well as no GC bias and no PCR amplification requirement. This review briefly summarized the technical principle and characteristics of nanopore sequencing, followed by discussing the application of nanopore sequencing techniques in the amplicon sequencing, metagenome sequencing and whole genome sequencing of environmental microorganisms. The advantages and challenges of nanopore sequencing in the application of environmental microbiology research were also analyzed.
Environmental Microbiology ; High-Throughput Nucleotide Sequencing ; Metagenome ; Nanopore Sequencing ; Nanopores

Hepatitis B virus ; classification ; genetics ; High-Throughput Nucleotide Sequencing

High-Throughput Nucleotide Sequencing ; Humans ; Rare Diseases ; genetics

We examine the role of big data and machine learning in cancer research. We describe an example in cancer research where gene-level data from The Cancer Genome Atlas (TCGA) consortium is interpreted using a pathway-level model. As the complexity of computational models increases, their sample requirements grow exponentially. This growth stems from the fact that the number of combinations of variables grows exponentially as the number of variables increases. Thus, a large sample size is needed. The number of variables in a computational model can be reduced by incorporating biological knowledge. One particularly successful way of doing this is by using available gene regulatory, signaling, metabolic, or context-specific pathway information. We conclude that the incorporation of existing biological knowledge is essential for the progress in using big data for cancer research.
Computer Simulation ; Genome ; High-Throughput Nucleotide Sequencing ; Humans ; Neoplasms

The big data from high throughput research disclosed 4V features: volume of data, variety of data, value for deep mining, and velocity of processing speed. Regarding the whole genome sequencing for human sample, at average 30x of coverage, a total of 100 GB of original data (compression FASTQ format) could be produced. Replying to the binary BAM format, a total of 150 GB data could be produced. In the analysis of high throughput data, we need to combine both clinical information and pathological features. In addition, the data sources of medical research involved in ethical and privacy of patients. At present, the costs are gradually cheaper. For example, a whole genome sequencing by Illumina X Ten with 30x coverage costs about 10,000 RMB, and RNA-seq costs 5000 RMB for a single sample. Therefore, cancer genome research provides opportunities for discovery of molecular targets, but also brings enormous challenges on the data integration and utilization. This article introduces methodologies for high throughput data analysis and processing, and explains possible application on molecular target discovery.
Computational Biology ; High-Throughput Nucleotide Sequencing ; Humans ; Neoplasms

OBJECTIVETo establish a hyperphenylalaninemia related genes screening method using Ion Torrent Personal Genome Machine (PGM) for early detection and differential diagnosis of hyperphenylalaninemia (HPA).

METHODSThree children with known HPA mutations and a healthy control were used for setting up the method. Ten children with HPA with known mutations were recruited for validating the method. Ion Ampliseq PCR was used to amplify the 5' and 3' untranslated region, coding sequence, and flanking introns of PAH, GCH1, PTS, QDPR, and PCBD1 genes. After the enrichment with the Ion OneTouch system, the products were sequenced by PGM. Data from the PGM were processed with Torrent Suite v2.2 software package. All variations were confirmed by Sanger sequencing.

RESULTSFor the 4 samples, the PGM output was 94.22 Mb, with approximately 99.5% of reads mapping to the target regions. Among these samples, we detected 74 variations (28 positions) including 6 known mutations. Compared with database and results of Sanger sequencing, 55 (18 positions) polymorphisms and 13 (4 positions) false positive calls were confirmed. For the 10 samples, all the known mutations were successfully identified.

CONCLUSIONIon Torrent PGM sequencing is suitable for screening genetic mutation underlying HPA from the perspective of metabolic pathways, which can meet the clinical demand for individualized diagnosis and treatment.

Bronchoscopy ; High-Throughput Nucleotide Sequencing ; Humans ; Lung ; Lung Neoplasms ; Metagenomics

The research on endophytes of medicinal plants mainly relies on the traditional culture and isolation methods. Because of their functions such as promoting host growth, improving stress resistance, promoting the accumulation of medicinal active ingredients or directly producing medicinal active ingredients, the endophytes of medicinal plants have gradually attracted wide attention. However, it was found that the strains isolated by traditional methods were not the true dominant endophytes of medicinal plants by comparing the results of traditional culture isolation with high-throughput sequencing. The blind and random nature of traditional methods leads to the lack of standards in terms of medium selection, culture time and interaction between species. On the contrary, high-throughput sequencing technology is an emerging molecular biology technology developed in recent decades. Due to its high resolution level and indepen-dent culture, it can be used for thorough analysis of the community structure and diversity of environmental microorganisms. Therefore, we proposed the strategy of using high-throughput sequencing technology to guide the traditional culture and isolation of endophytes from medicinal plants. Firstly, the endophytic structure and diversity of medicinal plants were completely clear by high-throughput sequencing technology, and the dominant endophytes of the host were unequivocal. Then according to the characteristics of each dominant endophytes design or query suitable medium for its growth to culture and isolation. Finally, the function of the isolates was studied. This method can prevent researchers from missing out on the important functional strains of the host, expand the research scope of endophytes of medicinal plants, and facilitate the in-depth excavation and utilization of endophytes of medicinal plants.
Endophytes/genetics* ; High-Throughput Nucleotide Sequencing ; Plants, Medicinal ; Research Design