Quantifying bacterial efflux within subcellular domains of Pseudomonas aeruginosa.

Molecular efflux is a mechanism through which bacteria actively expel undesirable substances. This is a crucial line of defense against toxic chemicals in harsh environments. Understanding how efflux works is critical for designing antimicrobial strategies. Though much is already known about efflux proteins, important details about the mechanisms of efflux (e.g., importance of specific subcellular domains and ejection rates) have yet to be experimentally quantified. Herein, we use the nonlinear optical technique, second harmonic light scattering, to simultaneously measure the efflux rates from the periplasm and cytosol of a Gram-negative bacterium. The influence of efflux on the uptake kinetics of a mild antimicrobial, malachite green (MG), by Pseudomonas aeruginosa was quantified. It is observed that efflux primarily occurs from the periplasm and is two orders of magnitude faster than from the cytosol. Efflux pumps activate to maintain MG concentrations in the periplasm below 1 µM, while efflux from the cytosol maintains MG concentration below 0.1 µM. Efflux pumps are shown to saturate when exogenous MG concentrations are greater than 25 µM, while the cytosol efflux function saturates at >15 µM. Finally, efflux pumps can simultaneously eject different compounds, as proven by experiments with both MG and hexane, a known effluxable compound.IMPORTANCEMolecular efflux pumps are a crucial defense mechanism that protects bacteria from an otherwise unchecked influx of toxic molecules present in the extracellular environment. The efflux functions constitute a significant hindrance to antimicrobial efficacy. While much is now known regarding the structure of these channels, knowledge of the influence of efflux in individual subcellular domains and the associated ejection rates is still lacking. Using the nonlinear optical technique, second-harmonic light scattering, we have measured the threshold concentrations for pump activation, saturation concentrations, and efflux rates from both the periplasm and cytosol in living Gram-negative bacteria. The quantified efflux data in the different subcellular compartments not only provide a clear mechanistic understanding but also are critical for developing antimicrobial strategies.

Chemical Method for Recovery and Regeneration of Graphene Oxide.

Graphene oxide (GO) has been developed as a very effective medium for filtration and removal of microbial contaminants in fuel. GO is capable of filtering out microorganisms without needing micrometer and submicrometer pores for filtration. Our previous studies showed that microorganisms are attracted by GO and bind irreversibly to GO without promoting bacterial growth. Therefore, GO was tested as a filter medium to remove microorganisms in fuel. The characterization results showed that GO removed microbes in diesel fuel with >99% efficiency. However, the synthesis of GO using Hummers' method is labor intensive and a time-consuming. We present in this paper an economical, less labor intensive and a simple chemical approach to recover GO after it has been used as a filtration medium for the removal of microorganisms in fuels. In the GO recovery process, microbial and fuel contaminated GO is washed with hexane to remove any fuel from the GO sample. The hexane-washed GO is further washed with acetone and mixed with ethanol to kill and remove any microorganisms. After washing with ethanol, the GO sample is sonicated in water to remove impurities and re-establish the oxygen functionalities. The final recovered-GO (rec-GO) is obtained after removing water by rotary evaporation. The chemical characterization of rec-GO showed that rec-GO is similar in both chemical and physical properties compared to freshly synthesized-GO (as-syn-GO). Rec-GO was shown to perform similarly to as-syn-GO in filtration of biocontaminated fuel. We estimate that our rec-GO is at least 90% cheaper than high quality commercially available GO.

Electrochemical biosensor for rapid detection of fungal contamination in fuel systems.

There is an increased demand for real-time monitoring of biological and biochemical processes. While most sensor research focuses on physiological conditions, less has been done towards developing real-time biosensors that can operate in and survive exposure to extreme environments and harsh chemicals such as fuel. One interesting application is monitoring microbial load in fuel tanks to prevent both fuel spoilage and biocorrosion. We developed a comprehensive method to enable the first reagentless, real-time, microbial sensor platform that is also fuel resistant. We first identified an extracellular protein epitope conserved in fuel-degrading fungi then used this epitope to develop a suitable biorecognition element (BRE) through biopanning of a 7-mer phage displayed peptide library. After demonstrating the BRE's affinity to fungi using molecular and fluorescence assays, we incorporated the BRE into a reagentless, real-time electrochemical sensing platform based on a self-assembled monolayer of peptide BREs and redox reporters. Finally, we incorporated this real-time electrochemical sensing platform into a microfluidic device. We demonstrated detection of Yarrowia lipolytica as low as 1 × 104 CFU/mL in a bath cell, and demonstrate a microfluidic cell that functions even after exposure to jet fuel. In summary, this work describes development of a fuel-resistant biosensor for monitoring microbial growth in extreme environments.

Metagenome-Assembled Genomes of 12 Bacterial Species from Biofouled Plastic Fabrics Harbor Multiple Genes for Degradation of Hydrocarbons.

We report the metagenome-assembled genomes (MAGs) of 12 different bacterial species recovered from environmental microbiomes associated with biofouled plastic fabrics. The MAGs have estimated sizes of 2.53 to 7.66 Mb with 3,229 to 9,289 proteins, 26.20% to 99.1% genome completeness, 48.9% to 72.6% G+C content, and multiple genes for hydrocarbon degradation.

Black Yeast Genomes Assembled from Plastic Fabric Metagenomes Reveal an Abundance of Hydrocarbon Degradation Genes.

We report the assembly and annotation of 10 different black yeast genomes from microbiome metagenomic data derived from biofouled plastic fabrics. The draft genomes are estimated to be 9 to 33.2 Mb, with 357 to 5,108 contigs and G+C contents of 43.9% to 57.4%, and they harbor multiple genes for hydrocarbon adaptation and degradation.

GC-MS hydrocarbon degradation profile data of Pseudomonas frederiksbergensis SI8, a bacterium capable of degrading aromatics at low temperatures.

The ability of the psychrotrophic bacterium Pseudomonas frederiksbergensis SI8 to grow and degrade aromatic hydrocarbons efficiently at low temperature is shown in this study. The robust growth of P. frederiksbergensis SI8 was demonstrated in jet fuel and an aromatic blend. The bacterium showed 2.5 to 3-fold faster growth in the aromatic blend than in jet fuel. The hydrocarbons degradation profile of P. frederiksbergensis SI8 at ambient temperature (i.e., 28 °C) and low temperature (i.e., 4 °C) was characterized by Gas Chromatography-Mass Spectrometry (GC-MS) analysis. GC-MS data demonstrated that P. frederiksbergensis SI8 is a novel psychrotrophic bacterium with the ability to degrade aromatic hydrocarbons at temperatures as low as 4 °C. Specifically, P. frederiksbergensis SI8 consumed toluene, ethylbenzene, n-propylbenzene and methyl ethyl benzene efficiently. The data presented here serves to characterize the hydrocarbon degradation profile of P. frederiksbergensis SI8 and corroborates the capacity of this bacterium to degrade aromatic hydrocarbons at low temperatures. The raw GC-MS data for the degradation of hydrocarbons by P. frederiksbergensis SI8 grown at 4 °C and 28 °C for 14 days have been deposited in Mendeley Data and can be retrieved from https://dx.doi.org/10.17632/z9292bvdmh.1 and https://dx.doi.org/10.17632/dp3sgwpj23.1. The datasets and raw data presented here were associated with the main research work "Metagenomic characterization reveals complex association of soil hydrocarbon-degrading bacteria" [1].

Shotgun metagenomic data of microbiomes on plastic fabrics exposed to harsh tropical environments.

The development of more affordable high-throughput DNA sequencing technologies and powerful bioinformatics is making of shotgun metagenomics a common tool for effective characterization of microbiomes and robust functional genomics. A shotgun metagenomic approach was applied in the characterization of microbial communities associated with plasticized fabric materials exposed to a harsh tropical environment for 14 months. High-throughput sequencing of TruSeq paired-end libraries was conducted using a whole-genome shotgun (WGS) approach on an Illumina HiSeq2000 platform generating 100 bp reads. A multifaceted bioinformatics pipeline was developed and applied to conduct quality control and trimming of raw reads, microbial classification, assembly of multi-microbial genomes, binning of assembled contigs to individual genomes, and prediction of microbial genes and proteins. The bioinformatic analysis of the large 161 Gb sequence dataset generated 3,314,688 contigs and 120 microbial genomes. The raw metagenomic data and the detailed description of the bioinformatics pipeline applied in data analysis provide an important resource for the genomic characterization of microbial communities associated with biodegraded plastic fabric materials. The raw shotgun metagenomics sequence data of microbial communities on plastic fabric materials have been deposited in MG-RAST (https://www.mg-rast.org/) under accession numbers: mgm4794685.3-mgm4794690.3. The datasets and raw data presented here were associated with the main research work "Metagenomic characterization of microbial communities on plasticized fabric materials exposed to harsh tropical environments" (Radwan et al., 2020).

Impact of Self-Assembled Monolayer Design and Electrochemical Factors on Impedance-Based Biosensing.

Real-time sensing of proteins, especially in wearable devices, remains a substantial challenge due to the need to convert a binding event into a measurable signal that is compatible with the chosen analytical instrumentation. Impedance spectroscopy enables real-time detection via either measuring electrostatic interactions or electron transfer reactions while simultaneously being amenable to miniaturization for integration into wearable form-factors. To create a more robust methodology for optimizing impedance-based sensors, additional fundamental studies exploring components influencing the design and implementation of these sensors are needed. This investigation addresses a sub-set of these issues by combining optical and electrochemical characterization to validate impedance-based sensor performance as a function of (1) biorecognition element density, (2) self-assembled monolayer chain length, (3) self-assembled monolayer charge density, (4) the electrochemical sensing mechanism and (5) the redox reporter selection. Using a pre-existing lysozyme aptamer and lysozyme analyte combination, we demonstrate a number of design criteria to advance the state-of-the-art in protein sensing. For this model system we demonstrated the following: First, denser self-assembled monolayers yielded substantially improved sensing results. Second, self-assembled monolayer composition, including both thickness and charge density, changed the observed peak position and peak current. Third, single frequency measurements, while less informative, can be optimized to replace multi-frequency measurements and in some cases (such as that with zwitterionic self-assembled monolayers) are preferred. Finally, various redox reporters traditionally not used in impedance sensing should be further explored. Collectively, these results can help limit bottlenecks associated with device development, enabling realization of next-generation impedance-based biosensing with customize sensor design for the specific application.

Draft Genome Sequence of Lecanicillium sp. Isolate LEC01, a Fungus Capable of Hydrocarbon Degradation.

Lecanicillium sp. isolate LEC01 is adapted to grow in the presence of jet fuel, employing genes involved in the degradation of alkanes and aromatic hydrocarbons. The draft genome is estimated at 31,407,988 bp and has 9,737 proteins, 50.0% G+C content, and high similarity to Lecanicillium sp. strain CCF 5233.

Draft Genome Sequence of Achromobacter spanius Strain 6, a Soil Bacterium Isolated from a Hydrocarbon-Degrading Microcosm.

Achromobacter spanius strain 6 is a Gram-negative soil bacterium isolated from a hydrocarbon-degrading microcosm. The draft genome sequence of A. spanius strain 6 is 6.57 Mb with a G+C content of 64.7% and 5,855 protein coding genes. Multiple genes involved in degradation of aromatics are present in this strain.

Draft Genome Sequence of Byssochlamys sp. Isolate BYSS01, a Filamentous Fungus Adapted to the Fuel Environment.

Byssochlamys sp. isolate BYSS01 (anamorph, Paecilomyces sp.), which was isolated from jet fuel, is highly adapted to grow in hydrocarbons, having predicted genes involved in degradation of n-alkanes, branched alkanes, and aromatic compounds. The draft genome size is estimated at 29 Mb, containing 8,509 proteins.

Draft Genome Sequence of Fusarium fujikuroi, a Fungus Adapted to the Fuel Environment.

Fusarium fujikuroi isolate FUS01 is highly adapted to grow in jet fuel with predicted genes involved in hydrocarbon catabolism and carbon assimilation. The draft genome size is estimated at 49 Mb containing 18,578 proteins with high similarity to that of F. fujikuroi isolate B14.

Draft Genome Sequence of Pseudomonas stutzeri Strain 19, an Isolate Capable of Efficient Degradation of Aromatic Hydrocarbons.

Pseudomonas stutzeri strain 19 is a Gram-negative bacterium capable of degrading aromatic hydrocarbons. The draft genome of P. stutzeri 19 is estimated to be 5.1 Mb, containing 4,652 protein-coding genes and a G+C content of 63.3%. Multiple genes responsible for the degradation of aromatics are present in this strain.

A comprehensive multi-omics approach uncovers adaptations for growth and survival of Pseudomonas aeruginosa on n-alkanes.

BACKGROUND: Examination of complex biological systems has long been achieved through methodical investigation of the system's individual components. While informative, this strategy often leads to inappropriate conclusions about the system as a whole. With the advent of high-throughput "omic" technologies, however, researchers can now simultaneously analyze an entire system at the level of molecule (DNA, RNA, protein, metabolite) and process (transcription, translation, enzyme catalysis). This strategy reduces the likelihood of improper conclusions, provides a framework for elucidation of genotype-phenotype relationships, and brings finer resolution to comparative genomic experiments. Here, we apply a multi-omic approach to analyze the gene expression profiles of two closely related Pseudomonas aeruginosa strains grown in n-alkanes or glycerol. RESULTS: The environmental P. aeruginosa isolate ATCC 33988 consumed medium-length (C10-C16) n-alkanes more rapidly than the laboratory strain PAO1, despite high genome sequence identity (average nucleotide identity >99%). Our data shows that ATCC 33988 induces a characteristic set of genes at the transcriptional, translational and post-translational levels during growth on alkanes, many of which differ from those expressed by PAO1. Of particular interest was the lack of expression from the rhl operon of the quorum sensing (QS) system, resulting in no measurable rhamnolipid production by ATCC 33988. Further examination showed that ATCC 33988 lacked the entire lasI/lasR arm of the QS response. Instead of promoting expression of QS genes, ATCC 33988 up-regulates a small subset of its genome, including operons responsible for specific alkaline proteases and sphingosine metabolism. CONCLUSION: This work represents the first time results from RNA-seq, microarray, ribosome footprinting, proteomics, and small molecule LC-MS experiments have been integrated to compare gene expression in bacteria. Together, these data provide insights as to why strain ATCC 33988 is better adapted for growth and survival on n-alkanes.

Transcriptomic Analyses Elucidate Adaptive Differences of Closely Related Strains of Pseudomonas aeruginosa in Fuel.

Pseudomonas aeruginosa can utilize hydrocarbons, but different strains have various degrees of adaptation despite their highly conserved genome. P. aeruginosa ATCC 33988 is highly adapted to hydrocarbons, while P. aeruginosa strain PAO1, a human pathogen, is less adapted and degrades jet fuel at a lower rate than does ATCC 33988. We investigated fuel-specific transcriptomic differences between these strains in order to ascertain the underlying mechanisms utilized by the adapted strain to proliferate in fuel. During growth in fuel, the genes related to alkane degradation, heat shock response, membrane proteins, efflux pumps, and several novel genes were upregulated in ATCC 33988. Overexpression of alk genes in PAO1 provided some improvement in growth, but it was not as robust as that of ATCC 33988, suggesting the role of other genes in adaptation. Expression of the function unknown gene PA5359 from ATCC 33988 in PAO1 increased the growth in fuel. Bioinformatic analysis revealed that PA5359 is a predicted lipoprotein with a conserved Yx(FWY)xxD motif, which is shared among bacterial adhesins. Overexpression of the putative resistance-nodulation-division (RND) efflux pump PA3521 to PA3523 increased the growth of the ATCC 33988 strain, suggesting a possible role in fuel tolerance. Interestingly, the PAO1 strain cannot utilize n-C8 and n-C10 The expression of green fluorescent protein (GFP) under the control of alkB promoters confirmed that alk gene promoter polymorphism affects the expression of alk genes. Promoter fusion assays further confirmed that the regulation of alk genes was different in the two strains. Protein sequence analysis showed low amino acid differences for many of the upregulated genes, further supporting transcriptional control as the main mechanism for enhanced adaptation.IMPORTANCE These results support that specific signal transduction, gene regulation, and coordination of multiple biological responses are required to improve the survival, growth, and metabolism of fuel in adapted strains. This study provides new insight into the mechanistic differences between strains and helpful information that may be applied in the improvement of bacterial strains for resistance to biotic and abiotic factors encountered during bioremediation and industrial biotechnological processes.

Draft Genome Sequence of Nocardioides luteus Strain BAFB, an Alkane-Degrading Bacterium Isolated from JP-7-Polluted Soil.

Nocardioides luteus strain BAFB is a Gram-positive bacterium that efficiently degrades C8 to C11 alkanes aerobically. The draft genome of N. luteus BAFB is 5.76 Mb in size, with 5,358 coding sequences and 69.9% G+C content. The genes responsible for alkane degradation are present in this strain.

Draft Genome Sequence of Gordonia sihwensis Strain 9, a Branched Alkane-Degrading Bacterium.

Gordonia sihwensis strain 9 is a Gram-positive bacterium capable of efficient aerobic degradation of branched and normal alkanes. The draft genome of G. sihwensis S9 is 4.16 Mb in size, with 3,686 coding sequences and 68.1% G+C content. Alkane monooxygenase and P-450 cytochrome genes required for alkane degradation are predicted in G. sihwensis S9.

Draft Genome Sequence of Pseudomonas frederiksbergensis SI8, a Psychrotrophic Aromatic-Degrading Bacterium.

Pseudomonas frederiksbergensis strain SI8 is a psychrotrophic bacterium capable of efficient aerobic degradation of aromatic hydrocarbons. The draft genome of P. frederiksbergensis SI8 is 6.57 Mb in size, with 5,904 coding sequences and 60.5% G+C content. The isopropylbenzene (cumene) degradation pathway is predicted to be present in P. frederiksbergensis SI8.

Draft Genome Sequence of Rhodovulum sp. Strain NI22, a Naphthalene-Degrading Marine Bacterium.

Rhodovulum sp. strain NI22 is a hydrocarbon-degrading member of the genus Rhodovulum. The draft genome of Rhodovulum sp. NI22 is 3.8 Mb in size, with 3,756 coding sequences and 64.4% G+C content. The catechol and gentisate pathways for naphthalene degradation are predicted to be present in Rhodovulum sp. NI22.