Cultivatable microbial biodiversity: gnawing at the Gordian knot

Rapid and inexpensive sorting of bacterial isolates may be achieved using Fourier transform infrared spectroscopy (FT-IR), a method that has hitherto been applied to identification and classification. The comprehensive characterization of environmental samples requires the isolation of large numbers of isolates using different growth media and growth conditions. In such cases, sorting the isolates is critical before isolates are subjected to more detailed studies. Using FT-IR, isolates are grown under standardized conditions, and 100 strains can be tested within less than 8 h. Chemotaxonomic and molecular characterization of members of clusters emerging from FT-IR analysis either at a level of spectral distance values below 20–30 (analysis of region 600–800 cm⁻¹, average linkage algorithm) or at spectral heterogeneity values below 75 (regions 1200–900, 3000–2798 and 901–698, scaling to first region, Ward's algorithm) reveals great similarities in fatty acids and 16S rDNA sequences. As judged from riboprinting analyses and fatty acid analyses, FT-IR analysis is able to unravel intraspecific subclustering. The example used in this study of 100 isolates from a mat system, Lake Fryxell, Dry Valleys, Antarctica, selected from a larger number of isolates, picked mainly on the basis of colony pigmentation and form, reveals the utility of the method for identifying the number of putative species quickly. The method described is able to select strains rapidly that represent clusters at the specific and intraspecific level for subsequent characterization.     

Phytochrome signaling: solving the Gordian knot with microbial relatives

Phytochromes encompass a diverse collection of biliproteins that regulate numerous photoresponses in plants and microorganisms. Whereas the plant versions have proven experimentally intractable for structural studies, the microbial forms have recently provided important insights into how these photoreceptors work at the atomic level. Here, we review the current understanding of these microbial phytochromes, which shows that they have a modular dimeric architecture that propagates light-driven rotation of the bilin to distal contacts between adjacent signal output domains. Surprising features underpinning this signaling include: a deeply buried chromophore; a knot and hairpin loop that stabilizes the photosensing domain; and an extended helical spine that translates conformational changes in the photosensing domain to the output domain. Conservation within the superfamily both in modular construction and sequence strongly suggests that higher plant phytochromes work similarly as light-regulated toggle switches.     

Untying the Gordian knot of creation: metaphors for the Human Genome Project in Greek newspapers

This article studies the metaphorical expressions used by newspapers to present the near completion of the Human Genome Project (HGP) to the Greek public in the year 2000. The analysis, based on cognitive metaphor theory, deals with the most frequent or captivating metaphors used to refer to the human genome, which give rise to both conventional and novel expressions. The majority of creative metaphorical expressions participate in the discourse of hope and promise propagated by the Greek media in an attempt to present the HGP and its outcome in a favorable light. Instances of the competing discourse of fear and danger are much rarer but can also be found in creative metaphorical expressions. Metaphors pertaining to the Greek culture or to ancient Greek mythology tend to carry a special rhetorical force. However, it will be shown that the Greek press strategically used most of the metaphors that circulated globally at the time, not only culture specific ones.     

Cutting the Gordian knot of plant genetics: retrieval of missing heritability in tomato

<正>A pan-genome can be defined as the non-redundant collection of genomic diversity within a single species. Although the single reference genomes have achieved extremely high continuity and completeness owing to the recent advances in single-molecule sequencing and physical mapping technologies, it is hard for a linear reference genome to capture all the diversity within a species.     

Unraveling the Gordian knot: genetics and the troubled road to effective therapeutics for Alzheimer’s disease

In the late 20th century, identification of the major protein components of amyloid plaques and neurofibrillary tangles provided a window into the molecular pathology of Alzheimer’s disease, ushering in an era of optimism that targeted therapeutics would soon follow. The amyloid-cascade hypothesis took hold very early, supported by discoveries that dominant mutations in APP, PSEN1, and PSEN2 cause the very rare, early-onset, familial forms of the disease. However, in the past decade, a stunning series of failed Phase-3 clinical trials, testing anti-amyloid antibodies or processing-enzyme inhibitors, prompts the question, What went wrong? The FDA’s recent controversial approval of aducanumab, despite widespread concerns about efficacy and safety, only amplifies the question. The assumption that common, late-onset Alzheimer’s is a milder form of familial disease was not adequately questioned. The differential timing of discoveries, including blood–brain–barrier-penetrant tracers for imaging of plaques and tangles, made it easy to focus on amyloid. Furthermore, the neuropathology community initially implemented Alzheimer’s diagnostic criteria based on plaques only. The discovery that MAPT mutations cause frontotemporal dementia with tauopathy made it even easier to overlook the tangles in Alzheimer’s. Many important findings were simply ignored. The accepted mouse models did not predict the human clinical trials data. Given this lack of pharmacological validity, input from geneticists in collaboration with neuroscientists is needed to establish criteria for valid models of Alzheimer’s disease. More generally, scientists using genetic model organisms as whole-animal bioassays can contribute to building the pathogenesis network map of Alzheimer’s disease.     

宏基因组学及其在口腔微生物研究中的应用

宏基因组是指环境中所有微生物的遗传物质总和。宏基因组学技术可以最大限度地利用环境中的微生物资源,受到了国内外微生物研究者的重点关注。口腔中寄居着大量的微生物群落,以往对口腔疾病微生物的研究大多局限于单纯的细菌培养技术,然而,由于培养技术的局限性,部分微生物很难或根本不能培养,宏基因组学技术打破了这一局限性,帮助人类发掘更丰富的口腔微生物资源。最近,以宏基因组学测序为基础的研究描绘出了口腔生态系统的图谱,越来越多的实验证明口腔微生物组在各种口腔疾病甚至全身系统性疾病中的重要作用。同时,这也为基于人类微生物组的诊断和治疗开辟了新的途径。本综述旨在说明宏基因组学是研究人类口腔疾病及全身疾病相关微生物的得力工具,而且具有广阔的发展前景,同时也讨论了宏基因组学在应用中有待克服的局限性。     

A diffusion gradient chamber for studying microbial behavior and separating microorganisms

The natural habitats of most microbes are dynamic and include spatial gradients of growth substrates, electron acceptors, pH, salts, and inhibitory compounds. To mimic this diffusive aspect of nature, we developed an analytical diffusion gradient chamber (DGC) that can be used to separate, enrich for, isolate, and study the behavior of microorganisms. The chamber is a polycarbonate box containing an arena (5 by 5 by 2 cm) into which is cast a semisolid growth medium. Continuously replenished solute reservoirs positioned on each side of the arena but separated from it by a porous membrane enable the formation throughout the gel of multiple, intersecting gradients of solutes in two dimensions. With glucose as the solute, a gradient which spanned a 100-fold range in concentration was established across the arena in about 4 days. The shape of the glucose gradient was accurately predicted by a mathematical model based on Fickian diffusion. The growth and migratory behavior of Escherichia coli in response to imposed gradients of attractants (aspartate, alpha-methyl aspartate, and serine) and a repellent (valine) were examined. Cells responded in predictable ways to such gradients by forming distinctive growth and migration patterns in the DGC. This was true for wild-type E. coli as well as specific chemotaxis and motility mutants. The patterns yielded information about the threshold concentration of chemoeffectors needed to elicit a response as well as their saturating concentration. It was also evident that the metabolism of attractants significantly affected the gradients and, hence, the movement of cells. Finally, it was possible to separate E. coli and Pseudomonas fluorescens in the DGC on the basis of their differential responses to gradients of various chemoeffectors.     

Signal Processing for Metagenomics: Extracting Information from the Soup

Traditionally, studies in microbial genomics have focused on single-genomes from cultured species, thereby limiting their focus to the small percentage of species that can be cultured outside their natural environment. Fortunately, recent advances in high-throughput sequencing and computational analyses have ushered in the new field of metagenomics, which aims to decode the genomes of microbes from natural communities without the need for cultivation. Although metagenomic studies have shed a great deal of insight into bacterial diversity and coding capacity, several computational challenges remain due to the massive size and complexity of metagenomic sequence data. Current tools and techniques are reviewed in this paper which address challenges in 1) genomic fragment annotation, 2) phylogenetic reconstruction, 3) functional classification of samples, and 4) interpreting complementary metaproteomics and metametabolomics data. Also surveyed are important applications of metagenomic studies, including microbial forensics and the roles of microbial communities in shaping human health and soil ecology.     

宏基因组学:土壤微生物研究的新策略

土壤中多数微生物不可培养,这限制了微生物资源的开发利用。宏基因组学方法在开发和利用不可培养微生物资源方面有巨大潜力,可以将其运用到土壤微生物学研究中。对土壤宏基因组DNA的提取、宏基因组文库的构建和筛选等方面的研究现状和进展进行了简要综述。     

NeSSM: A Next-Generation Sequencing Simulator for Metagenomics

Background

Metagenomics can reveal the vast majority of microbes that have been missed by traditional cultivation-based methods. Due to its extremely wide range of application areas, fast metagenome sequencing simulation systems with high fidelity are in great demand to facilitate the development and comparison of metagenomics analysis tools.

Results

We present here a customizable metagenome simulation system: NeSSM (Next-generation Sequencing Simulator for Metagenomics). Combining complete genomes currently available, a community composition table, and sequencing parameters, it can simulate metagenome sequencing better than existing systems. Sequencing error models based on the explicit distribution of errors at each base and sequencing coverage bias are incorporated in the simulation. In order to improve the fidelity of simulation, tools are provided by NeSSM to estimate the sequencing error models, sequencing coverage bias and the community composition directly from existing metagenome sequencing data. Currently, NeSSM supports single-end and pair-end sequencing for both 454 and Illumina platforms. In addition, a GPU (graphics processing units) version of NeSSM is also developed to accelerate the simulation. By comparing the simulated sequencing data from NeSSM with experimental metagenome sequencing data, we have demonstrated that NeSSM performs better in many aspects than existing popular metagenome simulators, such as MetaSim, GemSIM and Grinder. The GPU version of NeSSM is more than one-order of magnitude faster than MetaSim.

Conclusions

NeSSM is a fast simulation system for high-throughput metagenome sequencing. It can be helpful to develop tools and evaluate strategies for metagenomics analysis and it’s freely available for academic users at http://cbb.sjtu.edu.cn/~ccwei/pub/software/NeSSM.php.