Single-cell metagenomics: challenges and applications

With the development of high throughput sequencing and single-cell genomics technologies, many uncultured bacterial communities have been dissected by combining these two techniques. Especially, by simultaneously leveraging of single-cell genomics and metagenomics, researchers can greatly improve the efficiency and accuracy of obtaining whole genome information from complex microbial communities, which not only allow us to identify microbes but also link function to species, identify subspecies variations, study host-virus interactions and etc. Here, we review recent developments and the challenges need to be addressed in single-cell metagenomics, including potential contamination, uneven sequence coverage, sequence chimera, genome assembly and annotation. With the development of sequencing and computational methods, single-cell metagenomics will undoubtedly broaden its application in various microbiome studies.     

Genomic sequencing of single microbial cells from environmental samples

Recently developed techniques allow genomic DNA sequencing from single microbial cells [Lasken RS: Single-cell genomic sequencing using multiple displacement amplification. Curr Opin Microbiol 2007, 10:510-516]. Here, we focus on research strategies for putting these methods into practice in the laboratory setting. An immediate consequence of single-cell sequencing is that it provides an alternative to culturing organisms as a prerequisite for genomic sequencing. The microgram amounts of DNA required as template are amplified from a single bacterium by a method called multiple displacement amplification (MDA) avoiding the need to grow cells. The ability to sequence DNA from individual cells will likely have an immense impact on microbiology considering the vast numbers of novel organisms, which have been inaccessible unless culture-independent methods could be used. However, special approaches have been necessary to work with amplified DNA. MDA may not recover the entire genome from the single copy present in most bacteria. Also, some sequence rearrangements can occur during the DNA amplification reaction. Over the past two years many research groups have begun to use MDA, and some practical approaches to single-cell sequencing have been developed. We review the consensus that is emerging on optimum methods, reliability of amplified template, and the proper interpretation of 'composite' genomes which result from the necessity of combining data from several single-cell MDA reactions in order to complete the assembly. Preferred laboratory methods are considered on the basis of experience at several large sequencing centers where >70% of genomes are now often recovered from single cells. Methods are reviewed for preparation of bacterial fractions from environmental samples, single-cell isolation, DNA amplification by MDA, and DNA sequencing.     

De novo assembly of human genome at single-cell levels

Genome assembly has been benefited from long-read sequencing technologies with higher accuracy and higher continuity. However, most human genome assembly require large amount of DNAs from homogeneous cell lines without keeping cell heterogeneities, since cell heterogeneity could profoundly affect haplotype assembly results. Herein, using single-cell genome long-read sequencing technology (SMOOTH-seq), we have sequenced K562 and HG002 cells on PacBio HiFi and Oxford Nanopore Technologies (ONT) platforms and conducted de novo genome assembly. For the first time, we have completed the human genome assembly with high continuity (with NG50 of ∼2 Mb using 95 individual K562 cells) at single-cell levels, and explored the impact of different assemblers and sequencing strategies on genome assembly. With sequencing data from 30 diploid individual HG002 cells of relatively high genome coverage (average coverage ∼41.7%) on ONT platform, the NG50 can reach over 1.3 Mb. Furthermore, with the assembled genome from K562 single-cell dataset, more complete and accurate set of insertion events and complex structural variations could be identified. This study opened a new chapter on the practice of single-cell genome de novo assembly.     

Whole Genome Amplification and De novo Assembly of Single Bacterial Cells

Background

Single-cell genome sequencing has the potential to allow the in-depth exploration of the vast genetic diversity found in uncultured microbes. We used the marine cyanobacterium Prochlorococcus as a model system for addressing important challenges facing high-throughput whole genome amplification (WGA) and complete genome sequencing of individual cells.

Methodology/Principal Findings

We describe a pipeline that enables single-cell WGA on hundreds of cells at a time while virtually eliminating non-target DNA from the reactions. We further developed a post-amplification normalization procedure that mitigates extreme variations in sequencing coverage associated with multiple displacement amplification (MDA), and demonstrated that the procedure increased sequencing efficiency and facilitated genome assembly. We report genome recovery as high as 99.6% with reference-guided assembly, and 95% with de novo assembly starting from a single cell. We also analyzed the impact of chimera formation during MDA on de novo assembly, and discuss strategies to minimize the presence of incorrectly joined regions in contigs.

Conclusions/Significance

The methods describe in this paper will be useful for sequencing genomes of individual cells from a variety of samples.     

微生物单细胞基因组技术及其在环境微生物研究中的应用

单细胞及单细胞基因组学研究是近年生命科学研究的热点之一,微生物单细胞基因组学研究是继微生物元基因组学(又称宏基因组学,Metagenomics)之后新发展起来的,可有效获取环境中大量无法培养的微生物遗传信息的技术。微生物单细胞基因组技术包括单细胞获取、全基因组扩增、全基因组测序以及数据分析等步骤,目前该技术在环境微生物研究中的应用主要集中于探索未被元基因组技术或其它常规技术探测到的新型功能基因,或是对环境中物种丰度极小的未培养微生物的发现,以及对微生物细胞生命进化过程的研究等。本文对微生物单细胞基因组技术中单细胞获取和全基因组扩增所涉及到的不同方法以及应用此技术对环境微生物取得的主要研究进展进行综述。     

A Quantitative Comparison of Single-Cell Whole Genome Amplification Methods

Single-cell sequencing is emerging as an important tool for studies of genomic heterogeneity. Whole genome amplification (WGA) is a key step in single-cell sequencing workflows and a multitude of methods have been introduced. Here, we compare three state-of-the-art methods on both bulk and single-cell samples of E. coli DNA: Multiple Displacement Amplification (MDA), Multiple Annealing and Looping Based Amplification Cycles (MALBAC), and the PicoPLEX single-cell WGA kit (NEB-WGA). We considered the effects of reaction gain on coverage uniformity, error rates and the level of background contamination. We compared the suitability of the different WGA methods for the detection of copy-number variations, for the detection of single-nucleotide polymorphisms and for de-novo genome assembly. No single method performed best across all criteria and significant differences in characteristics were observed; the choice of which amplifier to use will depend strongly on the details of the type of question being asked in any given experiment.     

Single-cell genome-wide concurrent haplotyping and copy-number profiling through genotyping-by-sequencing

Single-cell whole-genome haplotyping allows simultaneous detection of haplotypes associated with monogenic diseases, chromosome copy-numbering and subsequently, has revealed mosaicism in embryos and embryonic stem cells. Methods, such as karyomapping and haplarithmisis, were deployed as a generic and genome-wide approach for preimplantation genetic testing (PGT) and are replacing traditional PGT methods. While current methods primarily rely on single-nucleotide polymorphism (SNP) array, we envision sequencing-based methods to become more accessible and cost-efficient. Here, we developed a novel sequencing-based methodology to haplotype and copy-number profile single cells. Following DNA amplification, genomic size and complexity is reduced through restriction enzyme digestion and DNA is genotyped through sequencing. This single-cell genotyping-by-sequencing (scGBS) is the input for haplarithmisis, an algorithm we previously developed for SNP array-based single-cell haplotyping. We established technical parameters and developed an analysis pipeline enabling accurate concurrent haplotyping and copy-number profiling of single cells. We demonstrate its value in human blastomere and trophectoderm samples as application for PGT for monogenic disorders. Furthermore, we demonstrate the method to work in other species through analyzing blastomeres of bovine embryos. Our scGBS method opens up the path for single-cell haplotyping of any species with diploid genomes and could make its way into the clinic as a PGT application.     

基于三代测序技术的微生物组学研究进展

微生物在人类生活中无处不在, 过去人们对微生物的认识仅停留在单菌培养和定性研究上, 而测序技术的发展极大地促进了微生物组学的研究。越来越多的证据表明: 人体共生微生物、特别是肠道微生物与人类健康息息相关。 二代测序技术凭借其高通量、高准确率和低成本的特点, 成为微生物组学研究中的主流测序技术。但是随着研究的深入, 二代测序技术的短读长(< 450 bp)增加了后续数据分析和基因组拼接难度, 也限制了该技术在未来研究中的应用。在此背景下, 第三代测序技术应运而生。第三代测序技术又称单分子测序, 能够直接对单个DNA分子进行实时测序, 而不需要经过PCR扩增。第三代测序技术的平均读长在2-10 kb左右, 最高可以达到2.2 Mb, 实现了长序列的高通量测序。凭借其超长的测序读长、无GC偏好性等优势, 三代测序技术为微生物基因组全长测序, 组装完整可靠的基因组提供了新的方法。本文在描述三代测序的技术特点和原理的基础上, 重点介绍了三代测序技术在微生物16S/18S rRNA基因测序、单菌的基因组组装以及宏基因组中的研究应用和进展。     

单细胞全基因组扩增技术与应用

同一组织中的细胞往往具有类似的结构和功能,然而通过对单个细胞进行测序分析后,发现每个细胞都具有一定异质性.单细胞全基因组扩增技术是进行单细胞测序的前提,该技术可用于揭示单细胞基因组结构差异,同时在肿瘤研究、发育生物学、微生物学等研究中发挥重要作用,并成为生命科学研究技术的热点之一.单细胞全基因组扩增技术的难点在于单细胞的分离和全基因组的扩增.本文介绍了单细胞全基因组扩增技术中常用的单细胞分离技术和单细胞全基因组扩增技术,并对各技术间的优缺点进行比较,同时着重讨论该技术在肿瘤研究、发育生物学和微生物学研究中的应用.     

Current challenges and solutions of de novo assembly

Background: Next-generation sequencing (NGS) technologies have fostered an unprecedented proliferation of high-throughput sequencing projects and a concomitant development of novel algorithms for the assembly of short reads. However, numerous technical or computational challenges in de novo assembly still remain, although many new ideas and solutions have been suggested to tackle the challenges in both experimental and computational settings.Results: In this review, we first briefly introduce some of the major challenges faced by NGS sequence assembly. Then, we analyze the characteristics of various sequencing platforms and their impact on assembly results. After that, we classify de novo assemblers according to their frameworks (overlap graph-based, de Bruijn graph-based and string graph-based), and introduce the characteristics of each assembly tool and their adaptation scene. Next, we introduce in detail the solutions to the main challenges of de novo assembly of next generation sequencing data, single-cell sequencing data and single molecule sequencing data. At last, we discuss the application of SMS long reads in solving problems encountered in NGS assembly.Conclusions: This review not only gives an overview of the latest methods and developments in assembly algorithms, but also provides guidelines to determine the optimal assembly algorithm for a given input sequencing data type.     

Multilocus sequence typing--what is resolved?

Nucleotide sequence-based methods for bacterial typing (multilocus sequence typing; MLST) allow rapid and global comparisons between results from different laboratories. Combining this advantage with the reduced cost of high throughput sequencing, increasing automation and the amenability of sequence data for evolutionary analysis, it seems inevitable that sequence-based typing will eventually predominate over gel-based methods such as pulsed-field gel electrophoresis (PFGE) for most bacterial species. The increasing availability of multiple genome sequences for single pathogenic species, and the recent development of many new MLST schemes, means that a re-examination of the utility of multilocus sequencing, and in particular the choice of gene loci, is now appropriate.     

The microbial pan-genome

A decade after the beginning of the genomic era, the question of how genomics can describe a bacterial species has not been fully addressed. Experimental data have shown that in some species new genes are discovered even after sequencing the genomes of several strains. Mathematical modeling predicts that new genes will be discovered even after sequencing hundreds of genomes per species. Therefore, a bacterial species can be described by its pan-genome, which is composed of a "core genome" containing genes present in all strains, and a "dispensable genome" containing genes present in two or more strains and genes unique to single strains. Given that the number of unique genes is vast, the pan-genome of a bacterial species might be orders of magnitude larger than any single genome.     

Efficient de novo assembly of single-cell bacterial genomes from short-read data sets

Whole genome amplification by the multiple displacement amplification (MDA) method allows sequencing of DNA from single cells of bacteria that cannot be cultured. Assembling a genome is challenging, however, because MDA generates highly nonuniform coverage of the genome. Here we describe an algorithm tailored for short-read data from single cells that improves assembly through the use of a progressively increasing coverage cutoff. Assembly of reads from single Escherichia coli and Staphylococcus aureus cells captures >91% of genes within contigs, approaching the 95% captured from an assembly based on many E. coli cells. We apply this method to assemble a genome from a single cell of an uncultivated SAR324 clade of Deltaproteobacteria, a cosmopolitan bacterial lineage in the global ocean. Metabolic reconstruction suggests that SAR324 is aerobic, motile and chemotaxic. Our approach enables acquisition of genome assemblies for individual uncultivated bacteria using only short reads, providing cell-specific genetic information absent from metagenomic studies.     

Bioinformatics challenges of new sequencing technology

New DNA sequencing technologies can sequence up to one billion bases in a single day at low cost, putting large-scale sequencing within the reach of many scientists. Many researchers are forging ahead with projects to sequence a range of species using the new technologies. However, these new technologies produce read lengths as short as 35-40 nucleotides, posing challenges for genome assembly and annotation. Here we review the challenges and describe some of the bioinformatics systems that are being proposed to solve them. We specifically address issues arising from using these technologies in assembly projects, both de novo and for resequencing purposes, as well as efforts to improve genome annotation in the fragmented assemblies produced by short read lengths.     

Benchmarking of single-virus genomics: a new tool for uncovering the virosphere

Metagenomics and single-cell genomics have enabled the discovery of relevant uncultured microbes. Recently, single-virus genomics (SVG), although still in an incipient stage, has opened new avenues in viral ecology by allowing the sequencing of one single virus at a time. The investigation of methodological alternatives and optimization of existing procedures for SVG is paramount to deliver high-quality genomic data. We report a sequencing dataset of viral single-amplified genomes (vSAGs) from cultured and uncultured viruses obtained by applying different conditions in each SVG step, from viral preservation and novel whole-genome amplification (WGA) to sequencing platforms and genome assembly. Sequencing data showed that cryopreservation and mild fixation were compatible with WGA, although fresh samples delivered better genome quality data. The novel TruPrime WGA, based on primase-polymerase features, and WGA-X employing a thermostable phi29 polymerase, were proven to be with sufficient sensitivity in SVG. The Oxford Nanopore (ON) sequencing platform did not provide a significant improvement of vSAG assembly compared to Illumina alone. Finally, the SPAdes assembler performed the best. Overall, our results represent a valuable genomic dataset that will help to standardized and advance new tools in viral ecology.     

Genome complexity of harmful microalgae

During the past decade, next generation sequencing (NGS) technologies have provided new insights into the diversity, dynamics, and metabolic pathways of natural microbial communities. But, these new techniques face challenges related to the genome size and level of genome complexity of the species under investigation. Moreover, the coverage depth and the short-read length achieved by NGS based approaches also represent a major challenge for assembly. These factors could limit the use of these high-throughput sequencing methods for species lacking a reference genome and characterized by a high level of complexity. In the present work, the evolutionary history, mainly consisting of gene transfer events from bacteria and unicellular eukaryotes to microalgae, including harmful species, is discussed and reviewed as it relates to NGS application in microbial communities, with a particular focus on harmful algal bloom species and dinoflagellates. In the context of genetic population studies, genotyping-by-sequencing (GBS), an NGS based approach, could be used for the discovery and analysis of single nucleotide polymorphisms (SNPs). The NGS technologies are still relatively new and require further improvement. Specifically, there is a need to develop and standardize tools and approaches to handle large data sets, which have to be used for the majority of HAB species characterized by evolutionary highly dynamic genomes.     

A short review of variants calling for single-cell-sequencing data with applications

The field of single-cell sequencing is fleetly expanding, and many techniques have been developed in the past decade. With this technology, biologists can study not only the heterogeneity between two adjacent cells in the same tissue or organ, but also the evolutionary relationships and degenerative processes in a single cell. Calling variants is the main purpose in analyzing single cell sequencing (SCS) data. Currently, some popular methods used for bulk-cell-sequencing data analysis are tailored directly to be applied in dealing with SCS data. However, SCS requires an extra step of genome amplification to accumulate enough quantity for satisfying sequencing needs. The amplification yields large biases and thus raises challenge for using the bulk-cell-sequencing methods. In order to provide guidance for the development of specialized analyzed methods as well as using currently developed tools for SNS, this paper aims to bridge the gap. In this paper, we firstly introduced two popular genome amplification methods and compared their capabilities. Then we introduced a few popular models for calling single-nucleotide polymorphisms and copy-number variations. Finally, break-through applications of SNS were summarized to demonstrate its potential in researching cell evolution.