The focus of this review is on the recent data from the omics approaches, measuring the presence of methylotrophs in natural environments. Both Bacteria and Archaea are considered. The data are discussed in the context of the current knowledge on the biochemistry of methylotrophy and the physiology of cultivated methylotrophs. One major issue discussed is the recent metagenomic data pointing toward the activity of “aerobic” methanotrophs, such as Methylobacter, in microoxic or hypoxic conditions. A related issue of the metabolic distinction between aerobic and “anaerobic” methylotrophy is addressed in the light of the genomic and metagenomic data for respective organisms. The role of communities, as opposed to single-organism activities in environmental cycling of single-carbon compounds, such as methane, is also discussed. In addition, the emerging issue of the role of non-traditional methylotrophs in global metabolism of single-carbon compounds and the role of methylotrophy pathways in non-methylotrophs is briefly mentioned.

Despite >130 years of microbial cultivation studies, many microorganisms remain resistant to traditional cultivation approaches, including numerous candidate phyla of bacteria and archaea. Unraveling the mysteries of these candidate phyla is a grand challenge in microbiology and is especially important in habitats where they are abundant, including some extreme environments and low-energy ecosystems. Over the past decade, parallel advances in DNA amplification, DNA sequencing and computing have enabled rapid progress on this problem, particularly through metagenomics and single-cell genomics. Although each approach suffers limitations, metagenomics and single-cell genomics are particularly powerful when combined synergistically. Studies focused on extreme environments have revealed the first substantial genomic information for several candidate phyla, encompassing putative acidophiles (Parvarchaeota), halophiles (Nanohaloarchaeota), thermophiles (Acetothermia, Aigarchaeota, Atribacteria, Calescamantes, Korarchaeota, and Fervidibacteria), and piezophiles (Gracilibacteria). These data have enabled insights into the biology of these organisms, including catabolic and anabolic potential, molecular adaptations to life in extreme environments, unique genomic features such as stop codon reassignments, and predictions about cell ultrastructure. In addition, the rapid expansion of genomic coverage enabled by these studies continues to yield insights into the early diversification of microbial lineages and the relationships within and between the phyla of Bacteria and Archaea. In the next 5 years, the genomic foliage within the tree of life will continue to grow and the study of yet-uncultivated candidate phyla will firmly transition into the post-genomic era.

The early history of life harbours many unresolved evolutionary questions, none more important than the genomic origin and cellular evolution of eukaryotes. An issue central to eukaryote origin concerns the position of eukaryotes in the tree of life and the relationship of the host lineage that acquired the mitochondrion some two billion years ago to lineages of modern-day archaea. Recent analyses indicate that the host lineage branches within the Archaea, prompting the search for novel archaeal lineages that can improve our understanding of the cellular evolution of eukaryotes. Here we give a brief review of the studies on Archaea, the tree of life and the cellular evolution of eukaryotes, which is followed by an overview of recent progress fueled by new genomic technologies and recent status of archaeal research in China. Future directions for the study of early evolution are considered.

Background

Prokaryotes dominate the biosphere and regulate biogeochemical processes essential to all life. Yet, our knowledge about their biology is for the most part limited to the minority that has been successfully cultured. Molecular techniques now allow for obtaining genome sequences of uncultivated prokaryotic taxa, facilitating in-depth analyses that may ultimately improve our understanding of these key organisms.

Results

We compared results from two culture-independent strategies for recovering bacterial genomes: single-amplified genomes and metagenome-assembled genomes. Single-amplified genomes were obtained from samples collected at an offshore station in the Baltic Sea Proper and compared to previously obtained metagenome-assembled genomes from a time series at the same station. Among 16 single-amplified genomes analyzed, seven were found to match metagenome-assembled genomes, affiliated with a diverse set of taxa. Notably, genome pairs between the two approaches were nearly identical (average 99.51% sequence identity; range 98.77–99.84%) across overlapping regions (30–80% of each genome). Within matching pairs, the single-amplified genomes were consistently smaller and less complete, whereas the genetic functional profiles were maintained. For the metagenome-assembled genomes, only on average 3.6% of the bases were estimated to be missing from the genomes due to wrongly binned contigs.

Conclusions

The strong agreement between the single-amplified and metagenome-assembled genomes emphasizes that both methods generate accurate genome information from uncultivated bacteria. Importantly, this implies that the research questions and the available resources are allowed to determine the selection of genomics approach for microbiome studies.

The development of culture-independent strategies to study microbial diversity and function has led to a revolution in microbial ecology, enabling us to address fundamental questions about the distribution of microbes and their influence on Earth’s biogeochemical cycles. This article discusses some of the progress that scientists have made with the use of so-called “omic” techniques (metagenomics, metatranscriptomics, and metaproteomics) and the limitations and major challenges these approaches are currently facing. These ‘omic methods have been used to describe the taxonomic structure of microbial communities in different environments and to discover new genes and enzymes of industrial and medical interest. However, microbial community structure varies in different spatial and temporal scales and none of the ‘omic techniques are individually able to elucidate the complex aspects of microbial communities and ecosystems. In this article we highlight the importance of a spatiotemporal sampling design, together with a multilevel ‘omic approach and a community analysis strategy (association networks and modeling) to examine and predict interacting microbial communities and their impact on the environment.

Metagenomics (also Environmental Genomics, Ecogenomics or Community Genomics) is an emerging approach to studying microbial communities in the environment. This relatively new technique enables studies of organisms that are not easily cultured in a laboratory, thus differing from traditional microbiology that relies almost entirely on cultured organisms. Metagenomics technology thus holds the premise of new depths of understanding of microbes and, importantly, is a new tool for addressing biotechnological problems, without tedious cultivation efforts. DNA sequencing technology has already made a significant breakthrough, and generation of gigabase-pairs of microbial DNA sequences is not posing a challenge any longer. However, conceptual advances in microbial science will not only rely on the availability of innovative sequencing platforms, but also on sequence-independent tools for getting an insight into the functioning of microbial communities. This is an important issue, as we know that even the best annotations of genomes and metagenomes only create hypotheses of the functionality and substrate spectra of encoded proteins which require experimental testing by classical disciplines such as physiology and biochemistry. In this review, we address the following question, how to take advantage of, and how can we improve the, metagenomic technology for accommodating the needs of microbial biologists and enzymologists?

This chapter focuses on how metagenomic data are applied to examine the genomic heterogeneity of natural microbial populations. It highlights the opportunities and challenges inherent to the approach and describes recently developed methods to maximally leverage the potential of these datasets while tackling some of the challenges. We describe how performing population genomic analyses using metagenomic data allows (1) resolution of ecologically and genetically cohesive populations in the environment, (2) tracking of evolutionary processes within them, and (3) application of metatranscriptomic and metaproteomic analyses to determine the in situ physiology of distinct populations. While challenges remain that are inherent to the approach, the current wave of new bioinformatic tools is starting to realize the theoretical potential of metagenomics to peer into the spatiotemporal dynamics of the genetic structure of natural populations.

Since the first two complete bacterial genome sequences were published in 1995, the science of bacteria has dramatically changed. Using third-generation DNA sequencing, it is possible to completely sequence a bacterial genome in a few hours and identify some types of methylation sites along the genome as well. Sequencing of bacterial genome sequences is now a standard procedure, and the information from tens of thousands of bacterial genomes has had a major impact on our views of the bacterial world. In this review, we explore a series of questions to highlight some insights that comparative genomics has produced. To date, there are genome sequences available from 50 different bacterial phyla and 11 different archaeal phyla. However, the distribution is quite skewed towards a few phyla that contain model organisms. But the breadth is continuing to improve, with projects dedicated to filling in less characterized taxonomic groups. The clustered regularly interspaced short palindromic repeats (CRISPR)-Cas system provides bacteria with immunity against viruses, which outnumber bacteria by tenfold. How fast can we go? Second-generation sequencing has produced a large number of draft genomes (close to 90 % of bacterial genomes in GenBank are currently not complete); third-generation sequencing can potentially produce a finished genome in a few hours, and at the same time provide methlylation sites along the entire chromosome. The diversity of bacterial communities is extensive as is evident from the genome sequences available from 50 different bacterial phyla and 11 different archaeal phyla. Genome sequencing can help in classifying an organism, and in the case where multiple genomes of the same species are available, it is possible to calculate the pan- and core genomes; comparison of more than 2000 Escherichia coli genomes finds an E. coli core genome of about 3100 gene families and a total of about 89,000 different gene families. Why do we care about bacterial genome sequencing? There are many practical applications, such as genome-scale metabolic modeling, biosurveillance, bioforensics, and infectious disease epidemiology. In the near future, high-throughput sequencing of patient metagenomic samples could revolutionize medicine in terms of speed and accuracy of finding pathogens and knowing how to treat them.

The current prokaryotic taxonomy classifies phenotypically and genotypically diverse microorganisms using a polyphasic approach. With advances in the next-generation sequencing technologies and computational tools for analysis of genomes, the traditional polyphasic method is complemented with genomic data to delineate and classify bacterial genera and species as an alternative to cumbersome and error-prone laboratory tests. This review discusses the applications of sequence-based tools and techniques for bacterial classification and provides a scheme for more robust and reproducible bacterial classification based on genomic data. The present review highlights promising tools and techniques such as ortho-Average Nucleotide Identity, Genome to Genome Distance Calculator and Multi Locus Sequence Analysis, which can be validly employed for characterizing novel microorganisms and assessing phylogenetic relationships. In addition, the review discusses the possibility of employing metagenomic data to assess the phylogenetic associations of uncultured microorganisms. Through this article, we present a review of genomic approaches that can be included in the scheme of taxonomy of bacteria and archaea based on computational and in silico advances to boost the credibility of taxonomic classification in this genomic era.

Over the past two decades, application of high-throughput technologies for molecular analysis, collectively referred to as omicsOmics , have revolutionized the field of biologyBiology . These technologies enable collecting large amounts of data on DNADNA and RNARNA sequences, protein and metabolite identities, which can then be incorporated into metabolic models that can simulate metabolisms. OmicsOmics have been applied to studying methanotrophyMethanotrophy for a long time, and progress in this area has been summarised previously, including recent reviews. In this chapter, we only highlight the very latest novel insights into methanotrophy through omicsOmics . Some of the highlights are the newly uncovered environmental dominance of the Methylobacter species Methylobacter species , the discovery of novel methanotroph taxa through metagenomeMetagenome -assembled genome reconstruction, further insights into the role of lanthanidesLanthanides in methanotrophy, and further details on detection of the presence and activities of different guilds of methanotrophs across geochemical gradientsGeochemical gradients . We also touch briefly on the novel developments in understanding of the communal function in methanotrophy, and on the role of model organisms in further advancements of our knowledge.