scholarly journals Microfluidic-based mini-metagenomics enables discovery of novel microbial lineages from complex environmental samples

2017 ◽  
Author(s):  
Feiqiao Brian Yu ◽  
Paul C. Blainey ◽  
Frederik Schulz ◽  
Tanja Woyke ◽  
Mark A. Horowitz ◽  
...  
Keyword(s):  
Single Cell ◽  
Statistical Power ◽  
Ad Hoc ◽  
Hot Spring ◽  
Genomic Structure ◽  
Metagenomic Data ◽  
Rigorous Approach ◽  
Environmental Selection ◽  
Wide Range ◽  
Genome Level

AbstractMetagenomics and single-cell genomics have enabled the discovery of many new genomes from previously unknown branches of life. However, extracting novel genomes from complex mixtures of metagenomic data can still be challenging and in many respects represents an ill-posed problem which is generally approached with ad hoc methods. Here we present a microfluidic-based mini-metagenomic method which offers a statistically rigorous approach to extract novel microbial genomes from complex samples. In addition, by generating 96 sub-samples from each environmental sample, this method maintains high throughput, reduces sample complexity, and preserves single-cell resolution. We used this approach to analyze two hot spring samples from Yellowstone National Park and extracted 29 new genomes larger than 0.5 Mbps. These genomes represent novel lineages at different taxonomic levels, including three deeply branching lineages. Functional analysis revealed that these organisms utilize diverse pathways for energy metabolism. The resolution of this mini-metagenomic method enabled accurate quantification of genome abundance, even for genomes less than 1% in relative abundance. Our analyses also revealed a wide range of genome level single nucleotide polymorphism (SNP) distributions with nonsynonymous to synonymous ratio indicative of low to moderate environmental selection. The scale, resolution, and statistical power of microfluidic-based mini-metagenomic make it a powerful tool to dissect the genomic structure microbial communities while effectively preserving the fundamental unit of biology, the single cell.

scholarly journals Microfluidic-based mini-metagenomics enables discovery of novel microbial lineages from complex environmental samples

eLife ◽  
2017 ◽  
Vol 6 ◽  
Author(s):  
Feiqiao Brian Yu ◽  
Paul C Blainey ◽  
Frederik Schulz ◽  
Tanja Woyke ◽  
Mark A Horowitz ◽  
...  
Keyword(s):  
Single Cell ◽  
Statistical Power ◽  
Ad Hoc ◽  
Hot Spring ◽  
Genomic Structure ◽  
Metagenomic Data ◽  
Rigorous Approach ◽  
Environmental Selection ◽  
Ill Posed ◽  
Genome Level

Metagenomics and single-cell genomics have enabled genome discovery from unknown branches of life. However, extracting novel genomes from complex mixtures of metagenomic data can still be challenging and represents an ill-posed problem which is generally approached with ad hoc methods. Here we present a microfluidic-based mini-metagenomic method which offers a statistically rigorous approach to extract novel microbial genomes while preserving single-cell resolution. We used this approach to analyze two hot spring samples from Yellowstone National Park and extracted 29 new genomes, including three deeply branching lineages. The single-cell resolution enabled accurate quantification of genome function and abundance, down to 1% in relative abundance. Our analyses of genome level SNP distributions also revealed low to moderate environmental selection. The scale, resolution, and statistical power of microfluidic-based mini-metagenomics make it a powerful tool to dissect the genomic structure of microbial communities while effectively preserving the fundamental unit of biology, the single cell.

scholarly journals Insights into the dynamics between viruses and their hosts in a hot spring microbial mat

2020 ◽  
Vol 14 (10) ◽  
pp. 2527-2541 ◽  
Author(s):  
Jessica K. Jarett ◽  
Mária Džunková ◽  
Frederik Schulz ◽  
Simon Roux ◽  
David Paez-Espino ◽  
...  
Keyword(s):  
Single Cell ◽  
Hot Spring ◽  
Current Knowledge ◽  
Single Cells ◽  
Metagenomic Data ◽  
Viral Genomes ◽  
Active Viral Replication ◽  
High Layer ◽  
Host Virus Interactions ◽  
Virus Interactions

Abstract Our current knowledge of host–virus interactions in biofilms is limited to computational predictions based on laboratory experiments with a small number of cultured bacteria. However, natural biofilms are diverse and chiefly composed of uncultured bacteria and archaea with no viral infection patterns and lifestyle predictions described to date. Herein, we predict the first DNA sequence-based host–virus interactions in a natural biofilm. Using single-cell genomics and metagenomics applied to a hot spring mat of the Cone Pool in Mono County, California, we provide insights into virus–host range, lifestyle and distribution across different mat layers. Thirty-four out of 130 single cells contained at least one viral contig (26%), which, together with the metagenome-assembled genomes, resulted in detection of 59 viruses linked to 34 host species. Analysis of single-cell amplification kinetics revealed a lack of active viral replication on the single-cell level. These findings were further supported by mapping metagenomic reads from different mat layers to the obtained host–virus pairs, which indicated a low copy number of viral genomes compared to their hosts. Lastly, the metagenomic data revealed high layer specificity of viruses, suggesting limited diffusion to other mat layers. Taken together, these observations indicate that in low mobility environments with high microbial abundance, lysogeny is the predominant viral lifestyle, in line with the previously proposed “Piggyback-the-Winner” theory.

scholarly journals Fungal communities from geothermal soils in Yellowstone National Park

2021 ◽  
Author(s):  
Anna Bazzicalupo ◽  
Sonya Erlandson ◽  
Margaret Branine ◽  
Lauren Ruffing ◽  
Megan Ratz ◽  
...  
Keyword(s):  
Environmental Factors ◽  
Yellowstone National Park ◽  
National Park ◽  
Statistical Power ◽  
Hot Spring ◽  
Fungal Communities ◽  
Fungal Community Composition ◽  
Saprotrophic Fungi ◽  
Wide Range ◽  
Geothermal Soils

Geothermal soils offer unique insight into the way extreme environmental factors shape communities of organisms. However, little is known about the fungi growing in these environments and in particular how localized steep abiotic gradients affect fungal diversity. We used metabarcoding to characterize soil fungi surrounding a hot spring-fed thermal creek with water up to ~85 C and pH ~10 in Yellowstone National Park. No soil variable we measured determined fungal community composition. However, soils with pH >8 had lower fungal richness and different fungal assemblages when compared to less extreme soils. Saprotrophic fungi community profile followed more closely overall community patterns while ectomycorrhizal fungi did not, highlighting potential differences in the factors that structure these different fungal trophic guilds. In addition, in vitro growth experiments in four target fungal species revealed a wide range of tolerances to pH levels but not to heat. Overall, our results documenting fungal communities within a few hundred meters suggest stronger statistical power and wider sampling are needed to untangle so many co-varying environmental factors affecting such diverse species communities.

scholarly journals The Effect of Spring Water Geochemistry on Copper Proteins in Tengchong Hot Springs, China

2020 ◽  
Vol 86 (13) ◽  
Author(s):  
Shreya Srivastava ◽  
Hailiang Dong ◽  
Brandon R. Briggs
Keyword(s):  
High Temperature ◽  
Binding Proteins ◽  
Hot Springs ◽  
Hot Spring ◽  
Metagenomic Data ◽  
Copper Proteins ◽  
Ph Gradients ◽  
Quinol Oxidase ◽  
Binding Domains ◽  
Wide Range

ABSTRACT Copper (Cu) is an essential trace metal cofactor for a variety of proteins; however, excess Cu is toxic to most organisms. Cu homeostasis is maintained by a complex machinery of Cu binding proteins that control the uptake, transport, sequestration, and efflux of Cu ions. Despite the importance of Cu binding proteins in electron transfer, substrate oxidation, superoxide dismutation, and denitrification, little information exists about microbial Cu utilization in extreme environments, where the geochemical conditions may affect Cu bioavailability. Using metagenomic data from 9 hot springs in Tengchong, China, which range in temperature from 42°C to 96°C and in pH from 2.3 to 9, the effects of pH, temperature, and spring geochemistry on the distribution of Cu binding domains of proteins and oxidoreductases were studied. Dissolved Cu and Cu binding domains were detected across all temperature and pH gradients. Cu binding domains of cytochrome c oxidase subunits, heavy-metal-associated domains, and nitrous oxide reductase were detected at all sites. DoxB, a quinol oxidase, and other quinol oxidase subunits were the dominant Cu binding oxidoreductase subunits present at low-pH and high-temperature sites, whereas cbb3-type cytochrome c oxidase subunits were dominant at high-pH and high-temperature sites. Additionally, aa3-type cytochrome c oxidase was more prominent than cbb3-type cytochrome c oxidase under circumneutral-pH conditions. This suggests that the type of cytochrome c oxidase pathway and the Cu proteins employed by microbes to carry out important functions such as energy acquisition and efflux of excess Cu are affected by the physicochemical conditions of the springs. IMPORTANCE Copper is present in a variety of proteins and is required to carry out essential functions by all organisms. However, in hot spring environments, copper availability may be limited due to the high temperatures and the wide range in pH. The significance of our research is in relating the physicochemical environment to the distribution of copper proteins across hot spring environments, which provides increased understanding of primary functions and adaptions in these environments.

scholarly journals Clustering Single-Cell RNA-Seq Data with Regularized Gaussian Graphical Model

Genes ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 311
Author(s):  
Zhenqiu Liu
Keyword(s):  
Single Cell ◽  
Free Parameter ◽  
Graphical Model ◽  
Expression Patterns ◽  
Information Criterion ◽  
Log P ◽  
Rna Seq ◽  
Clustering Methods ◽  
Wide Range ◽  
Free Parameters

Single-cell RNA-seq (scRNA-seq) is a powerful tool to measure the expression patterns of individual cells and discover heterogeneity and functional diversity among cell populations. Due to variability, it is challenging to analyze such data efficiently. Many clustering methods have been developed using at least one free parameter. Different choices for free parameters may lead to substantially different visualizations and clusters. Tuning free parameters is also time consuming. Thus there is need for a simple, robust, and efficient clustering method. In this paper, we propose a new regularized Gaussian graphical clustering (RGGC) method for scRNA-seq data. RGGC is based on high-order (partial) correlations and subspace learning, and is robust over a wide-range of a regularized parameter λ. Therefore, we can simply set λ=2 or λ=log(p) for AIC (Akaike information criterion) or BIC (Bayesian information criterion) without cross-validation. Cell subpopulations are discovered by the Louvain community detection algorithm that determines the number of clusters automatically. There is no free parameter to be tuned with RGGC. When evaluated with simulated and benchmark scRNA-seq data sets against widely used methods, RGGC is computationally efficient and one of the top performers. It can detect inter-sample cell heterogeneity, when applied to glioblastoma scRNA-seq data.

scholarly journals The Cryptographic Complexity of Anonymous Coins: A Systematic Exploration

Cryptography ◽  
2021 ◽  
Vol 5 (1) ◽  
pp. 10
Author(s):  
Niluka Amarasinghe ◽  
Xavier Boyen ◽  
Matthew McKague
Keyword(s):  
Ad Hoc ◽  
Significant Rise ◽  
Security Models ◽  
Systematic Exploration ◽  
Wide Range ◽  
Distributed Transaction ◽  
Common Framework

The modern financial world has seen a significant rise in the use of cryptocurrencies in recent years, partly due to the convincing lure of anonymity promised by these schemes. Bitcoin, despite being considered as the most widespread among all, is claimed to have significant lapses in relation to its anonymity. Unfortunately, studies have shown that many cryptocurrency transactions can be traced back to their corresponding participants through the analysis of publicly available data, to which the cryptographic community has responded by proposing new constructions with improved anonymity claims. Nevertheless, the absence of a common metric for evaluating the level of anonymity achieved by these schemes has led to numerous disparate ad hoc anonymity definitions, making comparisons difficult. The multitude of these notions also hints at the surprising complexity of the overall anonymity landscape. In this study, we introduce such a common framework to evaluate the nature and extent of anonymity in (crypto) currencies and distributed transaction systems, thereby enabling one to make meaningful comparisons irrespective of their implementation. Accordingly, our work lays the foundation for formalizing security models and terminology across a wide range of anonymity notions referenced in the literature, while showing how “anonymity” itself is a surprisingly nuanced concept, as opposed to existing claims that are drawn upon at a higher level, thus missing out on the elemental factors underpinning anonymity.

Quantitative Content Analysis of the United Nations Seabed Debate: Methodology and a Continental Shelf Case Study

1970 ◽  
Vol 24 (3) ◽  
pp. 479-502 ◽  
Author(s):  
R. L. Friedheim ◽  
J. B. Kadane
Keyword(s):  
United Nations ◽  
Continental Shelf ◽  
Ad Hoc ◽  
Mineral Resources ◽  
Outer Edge ◽  
General Assembly ◽  
Wide Range ◽  
The Subject ◽  
The United Nations

International arrangements for the uses of the ocean have been the subject of long debate within the United Nations since a speech made by Ambassador Arvid Pardo of Malta before the General Assembly in 1967. Issues in question include the method of delimiting the outer edge of the legal continental shelf; the spectrum of ocean arms control possibilities; proposals to create a declaration of principles governing the exploration for, and the exploitation of, seabed mineral resources with the promise that exploitation take place only if it “benefits mankind as a whole,” especially the developing states; and consideration of schemes to create international machinery to regulate, license, or own the resources of the seabed and subsoil. The discussions and debates began in the First (Political and Security) Committee of the 22nd General Assembly and proceeded through an ad hoc committee to the 23rd and 24th assembly plenary sessions. The creation of a permanent committee on the seabed as a part of the General Assembly's machinery attests to the importance members of the United Nations attribute to ocean problems. Having established the committee, they will be faced soon with the necessity of reaching decisions. The 24th General Assembly, for example, passed a resolution requesting the Secretary-General to ascertain members' attitudes on the convening of a new international conference to deal with a wide range of law of the sea problems.

scholarly journals Genome-Wide Identification and Comparative Analysis for OPT Family Genes in Panax ginseng and Eleven Flowering Plants

Molecules ◽  
2018 ◽  
Vol 24 (1) ◽  
pp. 15 ◽  
Author(s):  
He Su ◽  
Yang Chu ◽  
Junqi Bai ◽  
Lu Gong ◽  
Juan Huang ◽  
...  
Keyword(s):  
Transcription Factors ◽  
Panax Ginseng ◽  
Expression Patterns ◽  
Flowering Plants ◽  
Functional Development ◽  
Wide Range ◽  
Organ Specific ◽  
Genome Level ◽  
Negative Links ◽  
Global Platform

Herb genomics and comparative genomics provide a global platform to explore the genetics and biology of herbs at the genome level. Panax ginseng C.A. Meyer is an important medicinal plant for a variety of bioactive chemical compounds of which the biosynthesis may involve transport of a wide range of substrates mediated by oligopeptide transporters (OPT). However, information about the OPT family in the plant kingdom is still limited. Only 17 and 18 OPT genes have been characterized for Oryza sativa and Arabidopsis thaliana, respectively. Additionally, few comprehensive studies incorporating the phylogeny, gene structure, paralogs evolution, expression profiling, and co-expression network between transcription factors and OPT genes have been reported for ginseng and other species. In the present study, we performed those analyses comprehensively with both online tools and standalone tools. As a result, we identified a total of 268 non-redundant OPT genes from 12 flowering plants of which 37 were from ginseng. These OPT genes were clustered into two distinct clades in which clade-specific motif compositions were considerably conservative. The distribution of OPT paralogs was indicative of segmental duplication and subsequent structural variation. Expression patterns based on two sources of RNA-Sequence datasets suggested that some OPT genes were expressed in both an organ-specific and tissue-specific manner and might be involved in the functional development of plants. Further co-expression analysis of OPT genes and transcription factors indicated 141 positive and 11 negative links, which shows potent regulators for OPT genes. Overall, the data obtained from our study contribute to a better understanding of the complexity of the OPT gene family in ginseng and other flowering plants. This genetic resource will help improve the interpretation on mechanisms of metabolism transportation and signal transduction during plant development for Panax ginseng.

scholarly journals The Development of an Effective Bacterial Single-Cell Lysis Method Suitable for Whole Genome Amplification in Microfluidic Platforms

Micromachines ◽  
2018 ◽  
Vol 9 (8) ◽  
pp. 367 ◽  
Author(s):  
Yuguang Liu ◽  
Dirk Schulze-Makuch ◽  
Jean-Pierre de Vera ◽  
Charles Cockell ◽  
Thomas Leya ◽  
...  
Keyword(s):  
Single Cell ◽  
Single Cells ◽  
Bacterial Species ◽  
Cell Manipulation ◽  
Microfluidic Platforms ◽  
Gram Positive ◽  
Gram Negative ◽  
Genome Amplification ◽  
Single Cell Sequencing ◽  
Wide Range

Single-cell sequencing is a powerful technology that provides the capability of analyzing a single cell within a population. This technology is mostly coupled with microfluidic systems for controlled cell manipulation and precise fluid handling to shed light on the genomes of a wide range of cells. So far, single-cell sequencing has been focused mostly on human cells due to the ease of lysing the cells for genome amplification. The major challenges that bacterial species pose to genome amplification from single cells include the rigid bacterial cell walls and the need for an effective lysis protocol compatible with microfluidic platforms. In this work, we present a lysis protocol that can be used to extract genomic DNA from both gram-positive and gram-negative species without interfering with the amplification chemistry. Corynebacterium glutamicum was chosen as a typical gram-positive model and Nostoc sp. as a gram-negative model due to major challenges reported in previous studies. Our protocol is based on thermal and chemical lysis. We consider 80% of single-cell replicates that lead to >5 ng DNA after amplification as successful attempts. The protocol was directly applied to Gloeocapsa sp. and the single cells of the eukaryotic Sphaerocystis sp. and achieved a 100% success rate.

scholarly journals Mito Hacker: a set of tools to enable high-throughput analysis of mitochondrial network morphology

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Ali Rohani ◽  
Jennifer A. Kashatus ◽  
Dane T. Sessions ◽  
Salma Sharmin ◽  
David F. Kashatus
Keyword(s):  
Single Cell ◽  
High Throughput ◽  
Data Science ◽  
Structural Information ◽  
Morphological Changes ◽  
Mitochondrial Morphology ◽  
Single Cell Level ◽  
Mitochondrial Network ◽  
Cell Level ◽  
Wide Range

Abstract Mitochondria are highly dynamic organelles that can exhibit a wide range of morphologies. Mitochondrial morphology can differ significantly across cell types, reflecting different physiological needs, but can also change rapidly in response to stress or the activation of signaling pathways. Understanding both the cause and consequences of these morphological changes is critical to fully understanding how mitochondrial function contributes to both normal and pathological physiology. However, while robust and quantitative analysis of mitochondrial morphology has become increasingly accessible, there is a need for new tools to generate and analyze large data sets of mitochondrial images in high throughput. The generation of such datasets is critical to fully benefit from rapidly evolving methods in data science, such as neural networks, that have shown tremendous value in extracting novel biological insights and generating new hypotheses. Here we describe a set of three computational tools, Cell Catcher, Mito Catcher and MiA, that we have developed to extract extensive mitochondrial network data on a single-cell level from multi-cell fluorescence images. Cell Catcher automatically separates and isolates individual cells from multi-cell images; Mito Catcher uses the statistical distribution of pixel intensities across the mitochondrial network to detect and remove background noise from the cell and segment the mitochondrial network; MiA uses the binarized mitochondrial network to perform more than 100 mitochondria-level and cell-level morphometric measurements. To validate the utility of this set of tools, we generated a database of morphological features for 630 individual cells that encode 0, 1 or 2 alleles of the mitochondrial fission GTPase Drp1 and demonstrate that these mitochondrial data could be used to predict Drp1 genotype with 87% accuracy. Together, this suite of tools enables the high-throughput and automated collection of detailed and quantitative mitochondrial structural information at a single-cell level. Furthermore, the data generated with these tools, when combined with advanced data science approaches, can be used to generate novel biological insights.

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