Genomic tools in bioremediation

Bioremediation is a process that uses microorganisms or their enzymes to remove pollutants from the environment. Generally, bioremediation technologies can be classified as in situ or ex situ. In situ bioremediation involves treating the contaminated material at the site while ex situ involves the removal of the contaminated material to be treated elsewhere. Like so much else in biology, the ease and availability of genomic data has created a new level of understanding this system. Bioremediation capabilities of the microbial population can be analyzed; not only by physiological parameters, but also by the use of genomic tools, and efficient remediation strategies can be planned. PCR and DNA- or oligonucleotide-based microarray technology is a powerful functional genomics tool that allows researchers to view the physiology of a living cell from a comprehensive and dynamic molecular perspective. This paper explores the use of such tools in bioremediation process.     

Bioinformatics tools for cancer metabolomics

It is well known that significant metabolic change take place as cells are transformed from normal to malignant. This review focuses on the use of different bioinformatics tools in cancer metabolomics studies. The article begins by describing different metabolomics technologies and data generation techniques. Overview of the data pre-processing techniques is provided and multivariate data analysis techniques are discussed and illustrated with case studies, including principal component analysis, clustering techniques, self-organizing maps, partial least squares, and discriminant function analysis. Also included is a discussion of available software packages.     

Navigating freely-available software tools for metabolomics analysis

Introduction

The field of metabolomics has expanded greatly over the past two decades, both as an experimental science with applications in many areas, as well as in regards to data standards and bioinformatics software tools. The diversity of experimental designs and instrumental technologies used for metabolomics has led to the need for distinct data analysis methods and the development of many software tools.

Objectives

To compile a comprehensive list of the most widely used freely available software and tools that are used primarily in metabolomics.

Methods

The most widely used tools were selected for inclusion in the review by either ≥ 50 citations on Web of Science (as of 08/09/16) or the use of the tool being reported in the recent Metabolomics Society survey. Tools were then categorised by the type of instrumental data (i.e. LC–MS, GC–MS or NMR) and the functionality (i.e. pre- and post-processing, statistical analysis, workflow and other functions) they are designed for.

Results

A comprehensive list of the most used tools was compiled. Each tool is discussed within the context of its application domain and in relation to comparable tools of the same domain. An extended list including additional tools is available at https://github.com/RASpicer/MetabolomicsTools which is classified and searchable via a simple controlled vocabulary.

Conclusion

This review presents the most widely used tools for metabolomics analysis, categorised based on their main functionality. As future work, we suggest a direct comparison of tools’ abilities to perform specific data analysis tasks e.g. peak picking.

     

Alpine microorganisms: useful tools for low-temperature bioremediation

Cold environments, including polar and alpine regions, are colonized by a wide diversity of microorganisms able to thrive at low temperatures. There is evidence of a wide range of metabolic activities in alpine cold ecosystems. Like polar microorganisms, alpine microorganisms play a key ecological role in their natural habitats for nutrient cycling, litter degradation, and many other processes. A number of studies have demonstrated the capacity of alpine microorganisms to degrade efficiently a wide range of hydrocarbons, including phenol, phenol-related compounds and petroleum hydrocarbons, and the feasibility of low-temperature bioremediation of European alpine soils by stimulating the degradation capacity of indigenous microorganisms has also been shown.     

Proteomics and metabolomics: the molecular make-up of toxic aromatic pollutant bioremediation

Microbial-mediated attenuation of toxic aromatic pollutants offers great potential for the restoration of contaminated environments in an ecologically acceptable manner. However, incomplete biological information regarding the regulation of growth and metabolism in many microbial communities restricts progress in the site-specific mineralization process. In the postgenomic era, recent advances in MS have allowed enormous progress in proteomics and elucidated many complex biological interactions. These research forefronts are now expanding toward the analysis of low-molecular-weight primary and secondary metabolites analysis, i.e., metabolomics. The advent of 2-DE in conjunction with MS offers a promising approach to address the molecular mechanisms of bioremediation. The two fields of proteomics and metabolomics have thus far worked separately to identify proteins and primary and secondary metabolites during bioremediation. A simultaneous study combining functional proteomics and metabolomics, i.e., proteometabolomics would create a system-wide approach to studying site-specific microorganisms during active mineralization processes. This article deals with advances in environmental proteomics and metabolomics and advocates the simultaneous study of both technologies to implement cell-free bioremediation.     

Toward supportive data collection tools for plant metabolomics

Over recent years, a number of initiatives have proposed standard reporting guidelines for functional genomics experiments. Associated with these are data models that may be used as the basis of the design of software tools that store and transmit experiment data in standard formats. Central to the success of such data handling tools is their usability. Successful data handling tools are expected to yield benefits in time saving and in quality assurance. Here, we describe the collection of datasets that conform to the recently proposed data model for plant metabolomics known as ArMet (architecture for metabolomics) and illustrate a number of approaches to robust data collection that have been developed in collaboration between software engineers and biologists. These examples also serve to validate ArMet from the data collection perspective by demonstrating that a range of software tools, supporting data recording and data upload to central databases, can be built using the data model as the basis of their design.     

功能代谢组学技术在微生物研究中的应用

功能代谢组学是以代谢组学技术发现关键代谢物为基础,结合体内体外实验和分子生物学等技术手段,研究差异代谢物及相关蛋白、酶和基因的功能,从而揭示生物体内在的分子调控机制。功能代谢组学技术具有精准识别关键调控代谢物及其相关基因或酶的特性,近年来在微生物相关疾病的防控和工业化生产等方面受到了广泛的关注。本文介绍了功能代谢组学技术的分析流程、相关研究方法与平台及其在微生物研究方面的应用,其中重点阐述了真核、原核以及病毒微生物的代谢特性、调控靶点及相关防控策略等。最后,提出功能代谢组学研究在未来面临的问题与挑战,为后续功能代谢组学的研究与发展提供新的思路。     

The potential of mass spectrometry imaging in plant metabolomics: a review

Phytochemistry Reviews - Imaging mass spectrometry (MSI) has contributed important information to several scientific fields and more recently to the biological sciences. The use of MSI as an...     

Increasing rigor in NMR-based metabolomics through validated and open source tools

Opportunities and challenges ahead for NMR-based metabolomics.

     

A simple method for conducting laboratory treatability studies to assess potential for In situ bioremediation

Summary A simple, sealed flask system for conducting laboratory treatability studies to assess potential for in situ bioremediation was developed, evaluated, and compared to treatability studies which were open to the atmosphere. The treatability studies were conducted in 40 ml volatile organic analysis (VOA) vials fitted with Teflon septum caps. Contaminant loss was significantly less in the sealed-flasks relative to systems open to the atmosphere.     

The potential biomarkers of drug addiction: proteomic and metabolomics challenges

Drug addiction places a significant burden on society and individuals. Proteomics and metabolomics approaches pave the road for searching potential biomarkers to assist the diagnosis and treatment. This review summarized putative drug addiction-related biomarkers in proteomics and metabolomics studies and discussed challenges and prospects in future studies. Alterations of several hundred proteins and metabolites were reported when exposure to abused drug, which enriched in energy metabolism, oxidative stress response, protein modification and degradation, synaptic function and neurotrasmission, etc. Hsp70, peroxiredoxin-6 and α- and β-synuclein, as well as n-methylserotonin and purine metabolites, were promising as potential biomarker for drug addiction.     

Recent and potential developments of biofluid analyses in metabolomics

Metabolomics, one of the ‘omic’ sciences in systems biology, is the global assessment and validation of endogenous small-molecule metabolites within a biologic system. Analysis of these key metabolites in body fluids has become an important role to monitor the state of biological organisms and is a widely used diagnostic tool for disease. A majority of these metabolites are being applied to metabolic profiling of the biological samples, for example, plasma and whole blood, serum, urine, saliva, cerebrospinal fluid, synovial fluid, semen, and tissue homogenates. However, the recognition of the need for a holistic approach to metabolism led to the application of metabolomics to biological fluids for disease diagnostics. A recent surge in metabolomic applications which are probably more accurate than routine clinical practice, dedicated to characterizing the biological fluids. While developments in the analysis of biofluid samples encompassing an important impediment, it must be emphasized that these biofluids are complementary. Metabolomics provides potential advantages that classical diagnostic approaches do not, based on following discovery of a suite of clinically relevant biomarkers that are simultaneously affected by the disease. Emerging as a promising biofocus, metabolomics will drive biofluid analyses and offer great benefits for public health in the long-term.     

Cyanide bioremediation: the potential of engineered nitrilases

The cyanide-degrading nitrilases are of notable interest for their potential to remediate cyanide contaminated waste streams, especially as generated in the gold mining, pharmaceutical, and electroplating industries. This review provides a brief overview of cyanide remediation in general but with a particular focus on the cyanide-degrading nitrilases. These are of special interest as the hydrolysis reaction does not require secondary substrates or cofactors, making these enzymes particularly good candidates for industrial remediation processes. The genetic approaches that have been used to date for engineering improved enzymes are described; however, recent structural insights provide a promising new approach.

     

Untapped potential: exploiting fungi in bioremediation of hazardous chemicals

Fungi possess the biochemical and ecological capacity to degrade environmental organic chemicals and to decrease the risk associated with metals, metalloids and radionuclides, either by chemical modification or by influencing chemical bioavailability. Furthermore, the ability of these fungi to form extended mycelial networks, the low specificity of their catabolic enzymes and their independence from using pollutants as a growth substrate make these fungi well suited for bioremediation processes. However, despite dominating the living biomass in soil and being abundant in aqueous systems, fungi have not been exploited for the bioremediation of such environments. In this Review, we describe the metabolic and ecological features that make fungi suited for use in bioremediation and waste treatment processes, and discuss their potential for applications on the basis of these strengths.     

Marine bacteria: potential candidates for enhanced bioremediation

Bacteria are widespread in nature as they can adapt to any extreme environmental conditions and perform various physiological activities. Marine environments are one of the most adverse environments owing to their varying nature of temperature, pH, salinity, sea surface temperature, currents, precipitation regimes and wind patterns. Due to the constant variation of environmental conditions, the microorganisms present in that environment are more suitably adapted to the adverse conditions, hence, possessing complex characteristic features of adaptation. Therefore, the bacteria isolated from the marine environments are supposed to be better utilized in bioremediation of heavy metals, hydrocarbon and many other recalcitrant compounds and xenobiotics through biofilm formation and production of extracellular polymeric substances. Many marine bacteria have been reported to have bioremediation potential. The advantage of using marine bacteria for bioremediation in situ is the direct use of organisms in any adverse conditions without any genetic manipulation. This review emphasizes the utilization of marine bacteria in the field of bioremediation and understanding the mechanism behind acquiring the characteristic feature of adaptive responses.     

Hydrocarbon bioremediation potential of an unimpacted Kuwaiti oil-field environment

Seasonal variations in the hydrocarbon-degrading potential of soil samples from an unimpacted site in the Kuwaiti Burgan oil field environment were studied under mesophilic conditions. Hydrocarbon-degrading microorganisms occurred but varied all-year-round, and their numbers ranged from 1.3 x 10(7) to 9.3 x 10(7) CFU g(-1) dry soil, while hydrocarbon-degrading fungi ranged from 3.0 x 10(4) - 3.8 x 10(5) CFU g(-1) dry soil, depending on the sampling period. These hydrocarbon-degraders also comprised variable but generally high proportions of the total aerobic heterotrophic organisms (2 to > 98%) for bacteria and lower levels (7-9%) for fungi. The crude oil-degrading capacity of the oil-degrading populations (bacteria and fungi) ranged from 80-95% of the hexane-extractable fractions. Differential inhibition studies carried out on soil samples showed that bacteria were the greater contributors to hydrocarbon degradation (79-92%) than fungi. Pure hydrocarbon substrates, hexadecane and phenanthrene, were degraded to near completion after a 28-day incubation by both the bacterial and fungal portions of the soil flora.     

NMR-based metabolomics studies of human prostate cancer tissue

Introduction

Prostate cancer (PCa) is one of the most prevalent cancers in men worldwide. Serum prostate-specific antigen (PSA) remains the most used biomarker in the detection and management of patients with PCa, in spite of the problems related with its low specificity, false positive rate and overdiagnosis. Furthermore, PSA is unable to discriminate indolent from aggressive PCa, which can lead to overtreatment. Early diagnosed and treated PCa can have a good prognosis and is potentially curable. Therefore, the discovery of new biomarkers able to detect clinically significant aggressive PCa is urgently needed.

Methods

This revision was based on an electronic literature search, using Pubmed, with Nuclear Magnetic Resonance (NMR), tissue and prostate cancer as keywords. All metabolomic studies performed in PCa tissues by NMR spectroscopy, from 2007 until March 2018, were included in this review.

Results

In the context of cancer, metabolomics allows the analysis of the entire metabolic profile of cancer cells. Several metabolic alterations occur in cancer cells to sustain their abnormal rates of proliferation. NMR proved to be a suitable methodology for the evaluation of these metabolic alterations in PCa tissues, allowing to unveil alterations in citrate, spermine, choline, choline-related compounds, lactate, alanine and glutamate.

Conclusion

The study of the metabolic alterations associated with PCa progression, accomplished by the analysis of PCa tissue by NMR, offers a promising approach for elucidating biochemical pathways affected by PCa and also for discovering new clinical biomarkers. The main metabolomic alterations associated with PCa development and promising biomarker metabolites for diagnosis of PCa were outlined.