Culture-free genome-wide locus sequence typing (GLST) provides new perspectives on Trypanosoma cruzi dispersal and infection complexity.

Analysis of genetic polymorphism is a powerful tool for epidemiological surveillance and research. Powerful inference from pathogen genetic variation, however, is often restrained by limited access to representative target DNA, especially in the study of obligate parasitic species for which ex vivo culture is resource-intensive or bias-prone. Modern sequence capture methods enable pathogen genetic variation to be analyzed directly from host/vector material but are often too complex and expensive for resource-poor settings where infectious diseases prevail. This study proposes a simple, cost-effective 'genome-wide locus sequence typing' (GLST) tool based on massive parallel amplification of information hotspots throughout the target pathogen genome. The multiplexed polymerase chain reaction amplifies hundreds of different, user-defined genetic targets in a single reaction tube, and subsequent agarose gel-based clean-up and barcoding completes library preparation at under 4 USD per sample. Our study generates a flexible GLST primer panel design workflow for Trypanosoma cruzi, the parasitic agent of Chagas disease. We successfully apply our 203-target GLST panel to direct, culture-free metagenomic extracts from triatomine vectors containing a minimum of 3.69 pg/µl T. cruzi DNA and further elaborate on method performance by sequencing GLST libraries from T. cruzi reference clones representing discrete typing units (DTUs) TcI, TcIII, TcIV, TcV and TcVI. The 780 SNP sites we identify in the sample set repeatably distinguish parasites infecting sympatric vectors and detect correlations between genetic and geographic distances at regional (< 150 km) as well as continental scales. The markers also clearly separate TcI, TcIII, TcIV and TcV + TcVI and appear to distinguish multiclonal infections within TcI. We discuss the advantages, limitations and prospects of our method across a spectrum of epidemiological research.

Digitalization in microbiology - Paving the path to sustainable circular bioeconomy.

The transition to a sustainable bio-based circular economy requires cutting edge technologies that ensure economic growth with environmentally responsible action. This transition will only be feasible when the opportunities of digitalization are also exploited. Digital methods and big data handling have already found their way into life sciences and generally offer huge potential in various research areas. While computational analyses of microbial metagenome data have become state of the art, the true potential of bioinformatics remains mostly untapped so far. In this article we present challenges and opportunities of digitalization including multi-omics approaches in discovering and exploiting the microbial diversity of the planet with the aim to identify robust biocatalysts for application in sustainable bioprocesses as part of the transition from a fossil-based to a bio-based circular economy. This will contribute to solving global challenges, including utilization of natural resources, food supply, health, energy and the environment.

A restriction enzyme reduced representation sequencing approach for low-cost, high-throughput metagenome profiling.

Microbial community profiles have been associated with a variety of traits, including methane emissions in livestock. These profiles can be difficult and expensive to obtain for thousands of samples (e.g. for accurate association of microbial profiles with traits), therefore the objective of this work was to develop a low-cost, high-throughput approach to capture the diversity of the rumen microbiome. Restriction enzyme reduced representation sequencing (RE-RRS) using ApeKI or PstI, and two bioinformatic pipelines (reference-based and reference-free) were compared to bacterial 16S rRNA gene sequencing using repeated samples collected two weeks apart from 118 sheep that were phenotypically extreme (60 high and 58 low) for methane emitted per kg dry matter intake (n = 236). DNA was extracted from freeze-dried rumen samples using a phenol chloroform and bead-beating protocol prior to RE-RRS. The resulting sequences were used to investigate the repeatability of the rumen microbial community profiles, the effect of laboratory and analytical method, and the relationship with methane production. The results suggested that the best method was PstI RE-RRS analyzed with the reference-free approach, which accounted for 53.3±5.9% of reads, and had repeatabilities of 0.49±0.07 and 0.50±0.07 for the first two principal components (PC1 and PC2), phenotypic correlations with methane yield of 0.43±0.06 and 0.46±0.06 for PC1 and PC2, and explained 41±8% of the variation in methane yield. These results were significantly better than for bacterial 16S rRNA gene sequencing of the same samples (p<0.05) except for the correlation between PC2 and methane yield. A Sensitivity study suggested approximately 2000 samples could be sequenced in a single lane on an Illumina HiSeq 2500, meaning the current work using 118 samples/lane and future proposed 384 samples/lane are well within that threshold. With minor adaptations, our approach could be used to obtain microbial profiles from other metagenomic samples.

A review of 10 years of human microbiome research activities at the US National Institutes of Health, Fiscal Years 2007-2016.

The National Institutes of Health (NIH) is the primary federal government agency for biomedical research in the USA. NIH provides extensive support for human microbiome research with 21 of 27 NIH Institutes and Centers (ICs) currently funding this area through their extramural research programs. This analysis of the NIH extramural portfolio in human microbiome research briefly reviews the early history of this field at NIH, summarizes the program objectives and the resources developed in the recently completed 10-year (fiscal years 2007-2016) $215 M Human Microbiome Project (HMP) program, evaluates the scope and range of the $728 M NIH investment in extramural human microbiome research activities outside of the HMP over fiscal years 2012-2016, and highlights some specific areas of research which emerged from this investment. This analysis closes with a few comments on the technical needs and knowledge gaps which remain for this field to be able to advance over the next decade and for the outcomes of this research to be able to progress to microbiome-based interventions for treating disease and supporting health.

Population genomic screening of all young adults in a health-care system: a cost-effectiveness analysis.

PURPOSE: To consider the impact and cost-effectiveness of offering preventive population genomic screening to all young adults in a single-payer health-care system. METHODS: We modeled screening of 2,688,192 individuals, all adults aged 18-25 years in Australia, for pathogenic variants in BRCA1/BRCA2/MLH1/MSH2 genes, and carrier screening for cystic fibrosis (CF), spinal muscular atrophy (SMA), and fragile X syndrome (FXS), at 71% testing uptake using per-test costs ranging from AUD$200 to $1200 (~USD$140 to $850). Investment costs included genetic counseling, surveillance, and interventions (reimbursed only) for at-risk individuals/couples. Cost-effectiveness was defined below AUD$50,000/DALY (disability-adjusted life year) prevented, using an incremental cost-effectiveness ratio (ICER), compared with current targeted testing. Outcomes were cancer incidence/mortality, disease cases, and treatment costs reduced. RESULTS: Population screening would reduce variant-attributable cancers by 28.8%, cancer deaths by 31.2%, and CF/SMA/FXS cases by 24.8%, compared with targeted testing. Assuming AUD$400 per test, investment required would be between 4 and 5 times higher than current expenditure. However, screening would lead to substantial savings in medical costs and DALYs prevented, at a highly cost-effective ICER of AUD$4038/DALY. At AUD$200 per test, screening would approach cost-saving for the health system (ICER = AUD$22/DALY). CONCLUSION: Preventive genomic screening in early adulthood would be highly cost-effective in a single-payer health-care system, but ethical issues must be considered.

Miniaturization and optimization of 384-well compatible RNA sequencing library preparation.

Preparation of high-quality sequencing libraries is a costly and time-consuming component of metagenomic next generation sequencing (mNGS). While the overall cost of sequencing has dropped significantly over recent years, the reagents needed to prepare sequencing samples are likely to become the dominant expense in the process. Furthermore, libraries prepared by hand are subject to human variability and needless waste due to limitations of manual pipetting volumes. Reduction of reaction volumes, combined with sub-microliter automated dispensing of reagents without consumable pipette tips, has the potential to provide significant advantages. Here, we describe the integration of several instruments, including the Labcyte Echo 525 acoustic liquid handler and the iSeq and NovaSeq Illumina sequencing platforms, to miniaturize and automate mNGS library preparation, significantly reducing the cost and the time required to prepare samples. Through the use of External RNA Controls Consortium (ERCC) spike-in RNAs, we demonstrated the fidelity of the miniaturized preparation to be equivalent to full volume reactions. Furthermore, detection of viral and microbial species from cell culture and patient samples was also maintained in the miniaturized libraries. For 384-well mNGS library preparations, we achieved cost savings of over 80% in materials and reagents alone, and reduced preparation time by 90% compared to manual approaches, without compromising quality or representation within the library.

A robust, cost-effective method for DNA, RNA and protein co-extraction from soil, other complex microbiomes and pure cultures.

The soil microbiome is inherently complex with high biological diversity, and spatial heterogeneity typically occurring on the submillimetre scale. To study the microbial ecology of soils, and other microbiomes, biomolecules, that is, nucleic acids and proteins, must be efficiently and reliably co-recovered from the same biological samples. Commercial kits are currently available for the co-extraction of DNA, RNA and proteins but none has been developed for soil samples. We present a new protocol drawing on existing phenol-chloroform-based methods for nucleic acids co-extraction but incorporating targeted precipitation of proteins from the phenol phase. The protocol is cost-effective and robust, and easily implemented using reagents commonly available in laboratories. The method is estimated to be eight times cheaper than using disparate commercial kits for the isolation of DNA and/or RNA, and proteins, from soil. The method is effective, providing good quality biomolecules from a diverse range of soil types, with clay contents varying from 9.5% to 35.1%, which we successfully used for downstream, high-throughput gene sequencing and metaproteomics. Additionally, we demonstrate that the protocol can also be easily implemented for biomolecule co-extraction from other complex microbiome samples, including cattle slurry and microbial communities recovered from anaerobic bioreactors, as well as from Gram-positive and Gram-negative pure cultures.

MG-RAST version 4-lessons learned from a decade of low-budget ultra-high-throughput metagenome analysis.

As technologies change, MG-RAST is adapting. Newly available software is being included to improve accuracy and performance. As a computational service constantly running large volume scientific workflows, MG-RAST is the right location to perform benchmarking and implement algorithmic or platform improvements, in many cases involving trade-offs between specificity, sensitivity and run-time cost. The work in [Glass EM, Dribinsky Y, Yilmaz P, et al. ISME J 2014;8:1-3] is an example; we use existing well-studied data sets as gold standards representing different environments and different technologies to evaluate any changes to the pipeline. Currently, we use well-understood data sets in MG-RAST as platform for benchmarking. The use of artificial data sets for pipeline performance optimization has not added value, as these data sets are not presenting the same challenges as real-world data sets. In addition, the MG-RAST team welcomes suggestions for improvements of the workflow. We are currently working on versions 4.02 and 4.1, both of which contain significant input from the community and our partners that will enable double barcoding, stronger inferences supported by longer-read technologies, and will increase throughput while maintaining sensitivity by using Diamond and SortMeRNA. On the technical platform side, the MG-RAST team intends to support the Common Workflow Language as a standard to specify bioinformatics workflows, both to facilitate development and efficient high-performance implementation of the community's data analysis tasks.

Accuracy, limitations and cost efficiency of eDNA-based community survey in tropical frogs.

Rapid environmental change in highly biodiverse tropical regions demands efficient biomonitoring programmes. While existing metrics of species diversity and community composition rely on encounter-based survey data, eDNA recently emerged as alternative approach. Costs and ecological value of eDNA-based methods have rarely been evaluated in tropical regions, where high species richness is accompanied by high functional diversity (e.g., the use of different microhabitats by different species and life stages). We first tested whether estimation of tropical frogs' community structure derived from eDNA data is compatible with expert field assessments. Next, we evaluated whether eDNA is a financially viable solution for biodiversity monitoring in tropical regions. We applied eDNA metabarcoding to investigate frog species occurrence in five ponds in the Chiquitano dry forest region in Bolivia and compared our data with a simultaneous visual and audio encounter survey (VAES). We found that taxon lists and community structure generated with eDNA and VAES correspond closely, and most deviations are attributable to different species' life histories. Cost efficiency of eDNA surveys was mostly influenced by the richness of local fauna and the number of surveyed sites: VAES may be less costly in low-diversity regions, but eDNA quickly becomes more cost-efficient in high-diversity regions with many sites sampled. The results highlight that eDNA is suitable for large-scale biodiversity surveys in high-diversity areas if life history is considered, and certain precautions in sampling, genetic analyses and data interpretation are taken. We anticipate that spatially extensive, standardized eDNA biodiversity surveys will quickly emerge in the future.

The challenge of diagnostic metagenomics.

INTRODUCTION: Diagnostic metagenomics and its associated trail of publications are spreading across the world. Multiple clinical labs in the United States, Europe, and Asia have gone to considerable lengths to optimize and validate a range of protocols for agnostically detecting viral, bacterial, fungal, and eukaryotic parasite nucleic acid across a range of patient specimens to aid in diagnosis for particularly recalcitrant cases. Others see a role for diagnostic metagenomics as a frontline diagnostic to replace other microbiological testing. Areas covered: There are considerable barriers to adoption for diagnostic metagenomics, including analytical sensitivity, interpretation, actionability, turnaround time, antimicrobial susceptibility, clinical utility, laboratory workflow, trial comparators, cost, and reimbursement. Expert commentary: Metagenomics is unlikely to become 'one test to rule them all' any time soon, not least because it is not indicative of historical infection like some of the highest volume tests in the clinical virology lab, viral serologies. The high cost and low marginal utility compared to 'standard of care' diagnostics have forced metagenomics to be mostly used for last-ditch cases. However, waiting for such patients to declare themselves as being diagnostically challenging in turn likely lessens the diagnostic yield and actionability of the information. Significant reductions in the cost of metagenomic sequencing are required for it to move up in the diagnostic pipeline. This review covers these associated obstacles of metagenomics, arguing for a parsimonious role in last-ditch diagnostics and awaiting the answer of many outstanding questions regarding its adoption.

Illumina sequencing and assessment of new cost-efficient protocol for metagenomic-DNA extraction from environmental water samples.

In this study, the development and assessment of a modified, efficient, and cost-efficient protocol for mDNA (metagenomic DNA) extraction from contaminated water samples was attempted. The efficiency of the developed protocol was investigated in comparison to a well-established commercial kit (Epicentre, Metagenomic DNA Isolation Kit for Water). The comparison was in terms of degree of shearing, yield, purity, duration, suitability for polymerase chain reaction and next-generation sequencing in addition to the quality of next-generation sequencing data. The DNA yield obtained from the developed protocol was 2.6 folds higher than that of the commercial kit. No significant difference in the alpha (Observed species, Chao1, Simpson and PD whole tree) and beta diversity was found between the DNA samples extracted by the commercial kit and the developed protocol. The number of high-quality sequences of the samples extracted by the developed method was 20% higher than those obtained by the samples processed by the kit. The developed economic protocol successfully yielded high-quality pure mDNA compatible with complex molecular applications. Thus we propose the developed protocol as a gold standard for future metagenomic studies investigating a large number of samples.

Illumina sequencing and assessment of new cost-efficient protocol for metagenomic-DNA extraction from environmental water samples

Abstract In this study, the development and assessment of a modified, efficient, and cost-efficient protocol for mDNA (metagenomic DNA) extraction from contaminated water samples was attempted. The efficiency of the developed protocol was investigated in comparison to a well-established commercial kit (Epicentre, Metagenomic DNA Isolation Kit for Water). The comparison was in terms of degree of shearing, yield, purity, duration, suitability for polymerase chain reaction and next-generation sequencing in addition to the quality of next-generation sequencing data. The DNA yield obtained from the developed protocol was 2.6 folds higher than that of the commercial kit. No significant difference in the alpha (Observed species, Chao1, Simpson and PD whole tree) and beta diversity was found between the DNA samples extracted by the commercial kit and the developed protocol. The number of high-quality sequences of the samples extracted by the developed method was 20% higher than those obtained by the samples processed by the kit. The developed economic protocol successfully yielded high-quality pure mDNA compatible with complex molecular applications. Thus we propose the developed protocol as a gold standard for future metagenomic studies investigating a large number of samples.

Building a bio-based industry in the Middle East through harnessing the potential of the Red Sea biodiversity.

The incentive for developing microbial cell factories for production of fuels and chemicals comes from the ability of microbes to deliver these valuable compounds at a reduced cost and with a smaller environmental impact compared to the analogous chemical synthesis. Another crucial advantage of microbes is their great biological diversity, which offers a much larger "catalog" of molecules than the one obtainable by chemical synthesis. Adaptation to different environments is one of the important drives behind microbial diversity. We argue that the Red Sea, which is a rather unique marine niche, represents a remarkable source of biodiversity that can be geared towards economical and sustainable bioproduction processes in the local area and can be competitive in the international bio-based economy. Recent bioprospecting studies, conducted by the King Abdullah University of Science and Technology, have established important leads on the Red Sea biological potential, with newly isolated strains of Bacilli and Cyanobacteria. We argue that these two groups of local organisms are currently most promising in terms of developing cell factories, due to their ability to operate in saline conditions, thus reducing the cost of desalination and sterilization. The ability of Cyanobacteria to perform photosynthesis can be fully exploited in this particular environment with one of the highest levels of irradiation on the planet. We highlight the importance of new experimental and in silico methodologies needed to overcome the hurdles of developing efficient cell factories from the Red Sea isolates.

GPU-Acceleration of Sequence Homology Searches with Database Subsequence Clustering.

Sequence homology searches are used in various fields and require large amounts of computation time, especially for metagenomic analysis, owing to the large number of queries and the database size. To accelerate computing analyses, graphics processing units (GPUs) are widely used as a low-cost, high-performance computing platform. Therefore, we mapped the time-consuming steps involved in GHOSTZ, which is a state-of-the-art homology search algorithm for protein sequences, onto a GPU and implemented it as GHOSTZ-GPU. In addition, we optimized memory access for GPU calculations and for communication between the CPU and GPU. As per results of the evaluation test involving metagenomic data, GHOSTZ-GPU with 12 CPU threads and 1 GPU was approximately 3.0- to 4.1-fold faster than GHOSTZ with 12 CPU threads. Moreover, GHOSTZ-GPU with 12 CPU threads and 3 GPUs was approximately 5.8- to 7.7-fold faster than GHOSTZ with 12 CPU threads.

A Rapid and Economical Method for Efficient DNA Extraction from Diverse Soils Suitable for Metagenomic Applications.

A rapid, cost effective method of metagenomic DNA extraction from soil is a useful tool for environmental microbiology. The present work describes an improved method of DNA extraction namely "powdered glass method" from diverse soils. The method involves the use of sterile glass powder for cell lysis followed by addition of 1% powdered activated charcoal (PAC) as purifying agent to remove humic substances. The method yielded substantial DNA (5.87 ± 0.04 µg/g of soil) with high purity (A260/280: 1.76 ± 0.05) and reduced humic substances (A340: 0.047 ± 0.03). The quality of the extracted DNA was compared against five different methods based on 16S rDNA PCR amplification, BamHI digestion and validated using quantitative PCR. The digested DNA was used for a metagenomic library construction with the transformation efficiency of 4 X 106 CFU mL-1. Besides providing rapid, efficient and economical extraction of metgenomic DNA from diverse soils, this method's applicability is also demonstrated for cultivated organisms (Gram positive B. subtilis NRRL-B-201, Gram negative E. coli MTCC40, and a microalgae C. sorokiniana UTEX#1666).

Ensemble analysis of adaptive compressed genome sequencing strategies.

BACKGROUND: Acquiring genomes at single-cell resolution has many applications such as in the study of microbiota. However, deep sequencing and assembly of all of millions of cells in a sample is prohibitively costly. A property that can come to rescue is that deep sequencing of every cell should not be necessary to capture all distinct genomes, as the majority of cells are biological replicates. Biologically important samples are often sparse in that sense. In this paper, we propose an adaptive compressed method, also known as distilled sensing, to capture all distinct genomes in a sparse microbial community with reduced sequencing effort. As opposed to group testing in which the number of distinct events is often constant and sparsity is equivalent to rarity of an event, sparsity in our case means scarcity of distinct events in comparison to the data size. Previously, we introduced the problem and proposed a distilled sensing solution based on the breadth first search strategy. We simulated the whole process which constrained our ability to study the behavior of the algorithm for the entire ensemble due to its computational intensity. RESULTS: In this paper, we modify our previous breadth first search strategy and introduce the depth first search strategy. Instead of simulating the entire process, which is intractable for a large number of experiments, we provide a dynamic programming algorithm to analyze the behavior of the method for the entire ensemble. The ensemble analysis algorithm recursively calculates the probability of capturing every distinct genome and also the expected total sequenced nucleotides for a given population profile. Our results suggest that the expected total sequenced nucleotides grows proportional to log of the number of cells and proportional linearly with the number of distinct genomes. The probability of missing a genome depends on its abundance and the ratio of its size over the maximum genome size in the sample. The modified resource allocation method accommodates a parameter to control that probability. AVAILABILITY: The squeezambler 2.0 C++ source code is available at http://sourceforge.net/projects/hyda/.

Sequencing pools of individuals - mining genome-wide polymorphism data without big funding.

The analysis of polymorphism data is becoming increasingly important as a complementary tool to classical genetic analyses. Nevertheless, despite plunging sequencing costs, genomic sequencing of individuals at the population scale is still restricted to a few model species. Whole-genome sequencing of pools of individuals (Pool-seq) provides a cost-effective alternative to sequencing individuals separately. With the availability of custom-tailored software tools, Pool-seq is being increasingly used for population genomic research on both model and non-model organisms. In this Review, we not only demonstrate the breadth of questions that are being addressed by Pool-seq but also discuss its limitations and provide guidelines for users.

Ready to put metadata on the post-2015 development agenda? Linking data publications to responsible innovation and science diplomacy.

Metadata refer to descriptions about data or as some put it, "data about data." Metadata capture what happens on the backstage of science, on the trajectory from study conception, design, funding, implementation, and analysis to reporting. Definitions of metadata vary, but they can include the context information surrounding the practice of science, or data generated as one uses a technology, including transactional information about the user. As the pursuit of knowledge broadens in the 21(st) century from traditional "science of whats" (data) to include "science of hows" (metadata), we analyze the ways in which metadata serve as a catalyst for responsible and open innovation, and by extension, science diplomacy. In 2015, the United Nations Millennium Development Goals (MDGs) will formally come to an end. Therefore, we propose that metadata, as an ingredient of responsible innovation, can help achieve the Sustainable Development Goals (SDGs) on the post-2015 agenda. Such responsible innovation, as a collective learning process, has become a key component, for example, of the European Union's 80 billion Euro Horizon 2020 R&D Program from 2014-2020. Looking ahead, OMICS: A Journal of Integrative Biology, is launching an initiative for a multi-omics metadata checklist that is flexible yet comprehensive, and will enable more complete utilization of single and multi-omics data sets through data harmonization and greater visibility and accessibility. The generation of metadata that shed light on how omics research is carried out, by whom and under what circumstances, will create an "intervention space" for integration of science with its socio-technical context. This will go a long way to addressing responsible innovation for a fairer and more transparent society. If we believe in science, then such reflexive qualities and commitments attained by availability of omics metadata are preconditions for a robust and socially attuned science, which can then remain broadly respected, independent, and responsibly innovative. "In Sierra Leone, we have not too much electricity. The lights will come on once in a week, and the rest of the month, dark[ness]. So I made my own battery to power light in people's houses." Kelvin Doe (Global Minimum, 2012) MIT Visiting Young Innovator Cambridge, USA, and Sierra Leone "An important function of the (Global) R&D Observatory will be to provide support and training to build capacity in the collection and analysis of R&D flows, and how to link them to the product pipeline." World Health Organization (2013) Draft Working Paper on a Global Health R&D Observatory.

Toward more transparent and reproducible omics studies through a common metadata checklist and data publications.

Biological processes are fundamentally driven by complex interactions between biomolecules. Integrated high-throughput omics studies enable multifaceted views of cells, organisms, or their communities. With the advent of new post-genomics technologies, omics studies are becoming increasingly prevalent; yet the full impact of these studies can only be realized through data harmonization, sharing, meta-analysis, and integrated research. These essential steps require consistent generation, capture, and distribution of metadata. To ensure transparency, facilitate data harmonization, and maximize reproducibility and usability of life sciences studies, we propose a simple common omics metadata checklist. The proposed checklist is built on the rich ontologies and standards already in use by the life sciences community. The checklist will serve as a common denominator to guide experimental design, capture important parameters, and be used as a standard format for stand-alone data publications. The omics metadata checklist and data publications will create efficient linkages between omics data and knowledge-based life sciences innovation and, importantly, allow for appropriate attribution to data generators and infrastructure science builders in the post-genomics era. We ask that the life sciences community test the proposed omics metadata checklist and data publications and provide feedback for their use and improvement.

An efficient and economical method for extraction of DNA amenable to biotechnological manipulations, from diverse soils and sediments.

AIMS: An attempt was made to optimize a new protocol for isolation of pure metagenomic DNA from soil samples. METHODS AND RESULTS: Various chemicals (FeCl3 , MgCl2 , CaCl2 and activated charcoal) were tested for their efficacy in isolation of metagenomic DNA from different soil and compost samples. Among these trials, charcoal and MgCl2 when used in combination yielded highly pure DNA free from humic acids and other contaminants. The DNA extracted with the optimized protocol was readily digested, amplified and cloned. Moreover, compared with a well-established commercial DNA isolation kit (UltraClean™ Soil DNA Isolation Kit), our method for DNA isolation was found to be economical. This demonstrated that the method developed can be applied to a wide variety of soil samples and allows handling of multiple samples at a given time. CONCLUSIONS: The optimized protocol developed has successfully yielded pure metagenomic DNA amenable to biotechnological manipulations. SIGNIFICANCE AND IMPACT OF THE STUDY: A user-friendly and economical protocol for isolation of DNA from soil and compost samples has been developed.