Recent advances in culture-based gut microbiome research.

Gut microbes affect the physiology of their hosts. Studying their diversity and functions is thus of utmost importance as it will open new avenues towards the discovery of new biomolecules and the treatment of diseases. Gut microbiome research is currently boosted by the unification of metagenomics, which has dominated the field in the last two decades, and cultivation, which is experiencing a renaissance. Each of these approaches has advantages and drawbacks that can be overcome if used synergistically. In this brief article, we summarize recent literature and own studies on the cultivation of gut microbes, provide a succinct status quo of cultured fractions and collections of isolates, and give short opinions on challenges and next steps to take.

Intraspecific diversification of the crop wild relative Brassica cretica Lam. using demographic model selection.

BACKGROUND: Crop wild relatives (CWRs) contain genetic diversity, representing an invaluable resource for crop improvement. Many of their traits have the potential to help crops to adapt to changing conditions that they experience due to climate change. An impressive global effort for the conservation of various CWR will facilitate their use in crop breeding for food security. The genus Brassica is listed in Annex I of the International Treaty on Plant Genetic Resources for Food and Agriculture. Brassica oleracea (or wild cabbage), a species native to southern and western Europe, has become established as an important human food crop plant because of its large reserves stored over the winter in its leaves. Brassica cretica Lam. (Bc) is a CWR in the brassica group and B. cretica subsp. nivea (Bcn) has been suggested as a separate subspecies. The species Bc has been proposed as a potential gene donor to brassica crops, including broccoli, cabbage, cauliflower, oilseed rape, etc. RESULTS: We sequenced genomes of four Bc individuals, including two Bcn and two Bc. Demographic analysis based on our whole-genome sequence data suggests that populations of Bc are not isolated. Classification of the Bc into distinct subspecies is not supported by the data. Using only the non-coding part of the data (thus, the parts of the genome that has evolved nearly neutrally), we find the gene flow between different Bc population is recent and its genomic diversity is high. CONCLUSIONS: Despite predictions on the disruptive effect of gene flow in adaptation, when selection is not strong enough to prevent the loss of locally adapted alleles, studies show that gene flow can promote adaptation, that local adaptations can be maintained despite high gene flow, and that genetic architecture plays a fundamental role in the origin and maintenance of local adaptation with gene flow. Thus, in the genomic era it is important to link the selected demographic models with the underlying processes of genomic variation because, if this variation is largely selectively neutral, we cannot assume that a diverse population of crop wild relatives will necessarily exhibit the wide-ranging adaptive diversity required for further crop improvement.

Evolution of gene regulatory networks by means of selection and random genetic drift.

The evolution of a population by means of genetic drift and natural selection operating on a gene regulatory network (GRN) of an individual has not been scrutinized in depth. Thus, the relative importance of various evolutionary forces and processes on shaping genetic variability in GRNs is understudied. In this study, we implemented a simulation framework, called EvoNET, that simulates forward-in-time the evolution of GRNs in a population. The fitness effect of mutations is not constant, rather fitness of each individual is evaluated on the phenotypic level, by measuring its distance from an optimal phenotype. Each individual goes through a maturation period, where its GRN may reach an equilibrium, thus deciding its phenotype. Afterwards, individuals compete to produce the next generation. We examine properties of the GRN evolution, such as robustness against the deleterious effect of mutations and the role of genetic drift. We are able to confirm previous hypotheses regarding the effect of mutations and we provide new insights on the interplay between random genetic drift and natural selection.

Large-Scale Integration of Amplicon Data Reveals Massive Diversity within Saprospirales, Mostly Originating from Saline Environments.

The order Saprospirales, a group of bacteria involved in complex degradation pathways, comprises three officially described families: Saprospiraceae, Lewinellaceae, and Haliscomenobacteraceae. These collectively contain 17 genera and 31 species. The current knowledge on Saprospirales diversity is the product of traditional isolation methods, with the inherited limitations of culture-based approaches. This study utilized the extensive information available in public sequence repositories combined with recent analytical tools to evaluate the global evidence-based diversity of the Saprospirales order. Our analysis resulted in 1183 novel molecular families, 15,033 novel molecular genera, and 188 K novel molecular species. Of those, 7 novel families, 464 novel genera, and 1565 species appeared in abundances at ≥0.1%. Saprospirales were detected in various environments, such as saline water, freshwater, soil, various hosts, wastewater treatment plants, and other bioreactors. Overall, saline water was the environment showing the highest prevalence of Saprospirales, with bioreactors and wastewater treatment plants being the environments where they occurred with the highest abundance. Lewinellaceae was the family containing the majority of the most prevalent species detected, while Saprospiraceae was the family with the majority of the most abundant species found. This analysis should prime researchers to further explore, in a more targeted way, the Saprospirales proportion of microbial dark matter.

Taxonomy Informed Clustering, an Optimized Method for Purer and More Informative Clusters in Diversity Analysis and Microbiome Profiling.

Bacterial diversity is often analyzed using 16S rRNA gene amplicon sequencing. Commonly, sequences are clustered based on similarity cutoffs to obtain groups reflecting molecular species, genera, or families. Due to the amount of the generated sequencing data, greedy algorithms are preferred for their time efficiency. Such algorithms rely only on pairwise sequence similarities. Thus, sometimes sequences with diverse phylogenetic background are clustered together. In contrast, taxonomic classifiers use position specific taxonomic information in assigning a probable taxonomy to a given sequence. Here we introduce Taxonomy Informed Clustering (TIC), a novel approach that utilizes classifier-assigned taxonomy to restrict clustering to only those sequences that share the same taxonomic path. Based on this concept, we offer a complete and automated pipeline for processing of 16S rRNA amplicon datasets in diversity analyses. First, raw reads are processed to form denoised amplicons. Next, the denoised amplicons are taxonomically classified. Finally, the TIC algorithm progressively assigning clusters at molecular species, genus and family levels. TIC outperforms greedy clustering algorithms like USEARCH and VSEARCH in terms of clusters' purity and entropy, when using data from the Living Tree Project as test samples. Furthermore, we applied TIC on a dataset containing all Bifidobacteriaceae-classified sequences from the IMNGS database. Here, TIC identified evidence for 1000s of novel molecular genera and species. These results highlight the straightforward application of the TIC pipeline and superior results compared to former methods in diversity studies. The pipeline is freely available at: https://github.com/Lagkouvardos/TIC.