Metagenomic analysis of microbial consortia native to the Amazon, Highlands, and Galapagos regions of Ecuador with potential for wastewater remediation.

Native microbial consortia have been proposed for biological wastewater treatment, but their diversity and function remain poorly understood. This study investigated three native microalgae-bacteria consortia collected from the Amazon, Highlands, and Galapagos regions of Ecuador to assess their metagenomes and wastewater remediation potential. The consortia were evaluated for 12 days under light (LC) and continuous dark conditions (CDC) to measure their capacity for nutrient and organic matter removal from synthetic wastewater (SWW). Overall, all three consortia demonstrated higher nutrient removal efficiencies under LC than CDC, with the Amazon and Galapagos consortia outperforming the Highlands consortium in nutrient removal capabilities. Despite differences in α- and ß-diversity, microbial species diversity within and between consortia did not directly correlate with their nutrient removal capabilities. However, all three consortia were enriched with core taxonomic groups associated with wastewater remediation activities. Our analyses further revealed higher abundances for nutrient removing microorganisms in the Amazon and Galapagos consortia compared with the Highland consortium. Finally, this study also uncovered the contribution of novel microbial groups that enhance wastewater bioremediation processes. These groups have not previously been reported as part of the core microbial groups commonly found in wastewater communities, thereby highlighting the potential of investigating microbial consortia isolated from ecosystems of megadiverse countries like Ecuador.

Metagenomic investigations into the microbial consortia, degradation pathways, and enzyme systems involved in the biodegradation of plastics in a tropical lentic pond sediment.

The exploitation of exciting features of plastics for diverse applications has resulted in significant plastic waste generation, which negatively impacts environmental compartments, metabolic processes, and the well-being of aquatic ecosystems biota. A shotgun metagenomic approach was deployed to investigate the microbial consortia, degradation pathways, and enzyme systems involved in the degradation of plastics in a tropical lentic pond sediment (APS). Functional annotation of the APS proteome (ORFs) using the PlasticDB database revealed annotation of 1015 proteins of enzymes such as depolymerase, esterase, lipase, hydrolase, nitrobenzylesterase, chitinase, carboxylesterase, polyesterase, oxidoreductase, polyamidase, PETase, MHETase, laccase, alkane monooxygenase, among others involved in the depolymerization of the plastic polymers. It also revealed that polyethylene glycol (PEG), polyhydroxyalkanoates (PHA), polyhydroxybutyrate (PHB), polylactic acid (PLA), polybutylene adipate terephthalate (PBAT), polyethylene terephthalate (PET), and nylon have the highest number of annotated enzymes. Further annotation using the KEGG GhostKOALA revealed that except for terephthalate, all the other degradation products of the plastic polymers depolymerization such as glyoxylate, adipate, succinate, 1,4-butanediol, ethylene glycol, lactate, and acetaldehyde were further metabolized to intermediates of the tricarboxylic acid cycle. Taxonomic characterization of the annotated proteins using the AAI Profiler and BLASTP revealed that Pseudomonadota members dominate most plastic types, followed by Actinomycetota and Acidobacteriota. The study reveals novel plastic degraders from diverse phyla hitherto not reported to be involved in plastic degradation. This suggests that plastic pollution in aquatic environments is prevalent with well-adapted degrading communities and could be the silver lining in mitigating the impacts of plastic pollution in aquatic environments.

Towards consolidated bioprocessing of biomass and plastic substrates for semi-synthetic production of bio-poly(ethylene furanoate) (PEF) polymer using omics-guided construction of artificial microbial consortia.

Poly(ethylene furanoate) (PEF) plastic is a 100% renewable polyester that is currently being pursued for commercialization as the next-generation bio-based plastic. This is in line with growing demand for circular bioeconomy and new plastics economy that is aimed at minimizing plastic waste mismanagement and lowering carbon footprint of plastics. However, the current catalytic route for the synthesis of PEF is impeded with technical challenges including high cost of pretreatment and catalyst refurbishment. On the other hand, the semi-biosynthetic route of PEF plastic production is of increased biotechnological interest. In particular, the PEF monomers (Furan dicarboxylic acid and ethylene glycol) can be synthesized via microbial-based biorefinery and purified for subsequent catalyst-mediated polycondensation into PEF. Several bioengineering and bioprocessing issues such as efficient substrate utilization and pathway optimization need to be addressed prior to establishing industrial-scale production of the monomers. This review highlights current advances in semi-biosynthetic production of PEF monomers using consolidated waste biorefinery strategies, with an emphasis on the employment of omics-driven systems biology approaches in enzyme discovery and pathway construction. The roles of microbial protein transporters will be discussed, especially in terms of improving substrate uptake and utilization from lignocellulosic biomass, as well as from depolymerized plastic waste as potential bio-feedstock. The employment of artificial bioengineered microbial consortia will also be highlighted to provide streamlined systems and synthetic biology strategies for bio-based PEF monomer production using both plant biomass and plastic-derived substrates, which are important for circular and new plastics economy advances.

A molecular toolkit of cross-feeding strains for engineering synthetic yeast communities.

Engineered microbial consortia often have enhanced system performance and robustness compared with single-strain biomanufacturing production platforms. However, few tools are available for generating co-cultures of the model and key industrial host Saccharomyces cerevisiae. Here we engineer auxotrophic and overexpression yeast strains that can be used to create co-cultures through exchange of essential metabolites. Using these strains as modules, we engineered two- and three-member consortia using different cross-feeding architectures. Through a combination of ensemble modelling and experimentation, we explored how cellular (for example, metabolite production strength) and environmental (for example, initial population ratio, population density and extracellular supplementation) factors govern population dynamics in these systems. We tested the use of the toolkit in a division of labour biomanufacturing case study and show that it enables enhanced and tuneable antioxidant resveratrol production. We expect this toolkit to become a useful resource for a variety of applications in synthetic ecology and biomanufacturing.

Modularized Design and Construction of Tunable Microbial Consortia with Flexible Topologies.

Complex and fluid bacterial community compositions are critical to diversity, stability, and function. However, quantitative and mechanistic descriptions of the dynamics of such compositions are still lacking. Here, we develop a modularized design framework that allows for bottom-up construction and the study of synthetic bacterial consortia with different topologies. We showcase the microbial consortia design and building process by constructing amensalism and competition consortia using only genetic circuit modules to engineer different strains to form the community. Functions of modules and hosting strains are validated and quantified to calibrate dynamic parameters, which are then directly fed into a full mechanistic model to accurately predict consortia composition dynamics for both amensalism and competition without further fitting. More importantly, such quantitative understanding successfully identifies the experimental conditions to achieve coexistence composition dynamics. These results illustrate the process of both computationally and experimentally building up bacteria consortia complexity and hence achieve robust control of such fluid systems.

Unveiling bacterial consortium for xenobiotic biodegradation from Pichavaram mangrove forest soil: a metagenomic approach.

Pichavaram mangrove forest was established as a wetland of International Importance by Article 2.1 in April 2022 by the Ministry of Environment, Forest and Climate Change, India. Even though it is a conserved site, xenobiotic agrochemical leaching on the forest land during monsoon is inevitable. These threaten the microbial diversity in the environment. Xenobiotic degradation is achieved using bacterial consortia already acclimatised to this environment. This study aims to identify the indigenous microbial consortia able to degrade xenobiotic compounds such as fluorobenzoate, furfural, and steroids. Pichavaram mangrove metagenomic dataset was obtained by shotgun sequencing of soil DNA and processed using the automated tool SqueezeMeta. Further, the DIAMOND database provided the taxonomical classification of the microbes in each contig. With reference to the KEGG database, the selected xenobiotic degradation pathways were confirmed in the dataset. Of 1,253,029 total contigs, 1332, 72 and 1262 were involved in fluorobenzoate, furfural and steroid degradation, respectively. This study identified that microbial consortia comprising Marinobacter, Methyloceanibacter and Vibrio natriegens/Gramella sp. can degrade fluorobenzoate. While Afipia, Nitrosopumilus sp., and Phototrophicus methaneseepsis favour the degradation of furfural compound. The steroid degradation pathway possessed a plethora of bacteria belonging to the phylum Proteobacteria.

Tunable Dynamics in a Multistrain Transcriptional Pulse Generator.

One challenge in synthetic biology is the tuning of regulatory components within gene circuits to elicit a specific behavior. This challenge becomes more difficult in synthetic microbial consortia since each strain's circuit must function at the intracellular level and their combination must operate at the population level. Here we demonstrate that circuit dynamics can be tuned in synthetic consortia through the manipulation of strain fractions within the community. To do this, we construct a microbial consortium comprised of three strains of engineered Escherichia coli that, when cocultured, use homoserine lactone-mediated intercellular signaling to create a multistrain incoherent type-1 feedforward loop (I1-FFL). Like naturally occurring I1-FFL motifs in gene networks, this engineered microbial consortium acts as a pulse generator of gene expression. We demonstrate that the amplitude of the pulse can be easily tuned by adjusting the relative population fractions of the strains. We also develop a mathematical model for the temporal dynamics of the microbial consortium. This model allows us to identify population fractions that produced desired pulse characteristics, predictions that were confirmed for all but extreme fractions. Our work demonstrates that intercellular gene circuits can be effectively tuned simply by adjusting the starting fractions of each strain in the consortium.

Taxonomic and Predictive Functional Profile of Hydrocarbonoclastic Bacterial Consortia Developed at Three Different Temperatures.

Microbial community exhibit shift in composition in response to temperature variation. We report crude oil-degrading activity and high-throughput 16S rRNA gene sequencing (metagenome) profiles of four bacterial consortia enriched at three different temperatures in crude oil-amended Bushnell-Hass Medium from an oily sludge sediment. The consortia were referred to as O (4 ± 2 â„ƒ in 3% w/v crude oil), A (25 ± 2 â„ƒ in 1% w/v crude oil), H (25 ± 2 â„ƒ in 3% w/v crude oil), and X (45 ± 2 â„ƒ in 3% w/v crude oil). The hydrocarbon-degrading activity was highest for consortium A and H and lowest for consortium O. The metagenome profile revealed the predominance of Proteobacteria (62.12-1.25%) in each consortium, followed by Bacteroidota (18.94-37.77%) in the consortium O, A, and H. Contrarily, consortium X comprised 7.38% Actinomycetota, which was essentially low (< 0.09%) in other consortia, and only 0.41% Bacteroidota. The PICRUSt-based functional analysis predicted major functions associated with the metabolism and 5060 common KEGG Orthology (KOs). A total of 296 KOs were predicted exclusively in consortium X. Additionally, 247 KOs were predicted from xenobiotic biodegradation pathways. This study found that temperature had a stronger influence on the composition and function of the bacterial community than crude oil concentration.

Metagenomic Analysis of the Composition of Microbial Consortia Involved in Spruce Degradation over Time in Bialowieza Natural Forest.

Deadwood plays an important role in forest ecology; its degradation and, therefore, carbon assimilation is carried out by fungi and bacteria. To quantify the abundance and distribution of microbial taxa inhabiting dead spruce logs fallen over a span of 50 years and the soil beneath, we used taxonomic profiling with NGS sequencing of hypervariable DNA fragments of ITS1 and 16S V3-V4, respectively. The analysis of sequencing data revealed a high level of diversity in microbial communities participating in the degradation of spruce logs. Differences in the relative abundance of microbial taxa between the samples of the wood that died in 1974 and 2014, and of the soil in its immediate vicinity, were visible, especially at the genus level. Based on the Lefse analysis significantly higher numbers of classified bacterial taxa were observed in the wood and soil samples from 2014 (wood: 1974-18 and 2014-28 taxa; soil: 1974-8 and 2014-41 taxa) while the number of classified fungal taxa was significantly higher in the wood and soil samples from 1974 (wood: 1974-17 and 2014-9 taxa; soil: 1974-57 and 2014-28 taxa). Most of the bacterial and fungal amplicon sequence variants (ASVs) unique to wood were found in the samples from 1974, while those unique to soil were detected in the samples from 2014. The ATR-FTIR method supported by CHN analysis revealed physicochemical changes in deadwood induced by the activity of fungal and bacterial organisms.

Genome-resolved correlation mapping links microbial community structure to metabolic interactions driving methane production from wastewater.

Anaerobic digestion of municipal mixed sludge produces methane that can be converted into renewable natural gas. To improve economics of this microbial mediated process, metabolic interactions catalyzing biomass conversion to energy need to be identified. Here, we present a two-year time series associating microbial metabolism and physicochemistry in a full-scale wastewater treatment plant. By creating a co-occurrence network with thousands of time-resolved microbial populations from over 100 samples spanning four operating configurations, known and novel microbial consortia with potential to drive methane production were identified. Interactions between these populations were further resolved in relation to specific process configurations by mapping metagenome assembled genomes and cognate gene expression data onto the network. Prominent interactions included transcriptionally active Methanolinea methanogens and syntrophic benzoate oxidizing Syntrophorhabdus, as well as a Methanoregulaceae population and putative syntrophic acetate oxidizing bacteria affiliated with Bateroidetes (Tenuifilaceae) expressing the glycine cleavage bypass of the Wood-Ljungdahl pathway.

Functional conservation of microbial communities determines composition predictability in anaerobic digestion.

A major challenge in managing and engineering microbial communities is determining whether and how microbial community responses to environmental alterations can be predicted and explained, especially in microorganism-driven systems. We addressed this challenge by monitoring microbial community responses to the periodic addition of the same feedstock throughout anaerobic digestion, a typical microorganism-driven system where microorganisms degrade and transform the feedstock. The immediate and delayed response consortia were assemblages of microorganisms whose abundances significantly increased on the first or third day after feedstock addition. The immediate response consortia were more predictable than the delayed response consortia and showed a reproducible and predictable order-level composition across multiple feedstock additions. These results stood in both present (16 S rRNA gene) and potentially active (16 S rRNA) microbial communities and in different feedstocks with different biodegradability and were validated by simulation modeling. Despite substantial species variability, the immediate response consortia aligned well with the reproducible CH4 production, which was attributed to the conservation of expressed functions by the response consortia throughout anaerobic digestion, based on metatranscriptomic data analyses. The high species variability might be attributed to intraspecific competition and contribute to biodiversity maintenance and functional redundancy. Our results demonstrate reproducible and predictable microbial community responses and their importance in stabilizing system functions.

A structured evaluation of genome-scale constraint-based modeling tools for microbial consortia.

Harnessing the power of microbial consortia is integral to a diverse range of sectors, from healthcare to biotechnology to environmental remediation. To fully realize this potential, it is critical to understand the mechanisms behind the interactions that structure microbial consortia and determine their functions. Constraint-based reconstruction and analysis (COBRA) approaches, employing genome-scale metabolic models (GEMs), have emerged as the state-of-the-art tool to simulate the behavior of microbial communities from their constituent genomes. In the last decade, many tools have been developed that use COBRA approaches to simulate multi-species consortia, under either steady-state, dynamic, or spatiotemporally varying scenarios. Yet, these tools have not been systematically evaluated regarding their software quality, most suitable application, and predictive power. Hence, it is uncertain which tools users should apply to their system and what are the most urgent directions that developers should take in the future to improve existing capacities. This study conducted a systematic evaluation of COBRA-based tools for microbial communities using datasets from two-member communities as test cases. First, we performed a qualitative assessment in which we evaluated 24 published tools based on a list of FAIR (Findability, Accessibility, Interoperability, and Reusability) features essential for software quality. Next, we quantitatively tested the predictions in a subset of 14 of these tools against experimental data from three different case studies: a) syngas fermentation by C. autoethanogenum and C. kluyveri for the static tools, b) glucose/xylose fermentation with engineered E. coli and S. cerevisiae for the dynamic tools, and c) a Petri dish of E. coli and S. enterica for tools incorporating spatiotemporal variation. Our results show varying performance levels of the best qualitatively assessed tools when examining the different categories of tools. The differences in the mathematical formulation of the approaches and their relation to the results were also discussed. Ultimately, we provide recommendations for refining future GEM microbial modeling tools.

Whole genome sequencing analysis and Box-Behnken design for the optimization of the decolourization of mixture textile dyes by halotolerant microbial consortium.

The use of dyes in textile industries has resulted in substantially contaminated soil, water and ecosystem including fauna and flora. So, the application of eco-friendly approach for dyes removal is in great demand. The goal of this research was to develop and test a bacterial consortium for biodegrading dyes in artificial textile effluent (ATE) derived from mixture of Indigo carmine (40 mg/l); Malachite green (20 mg/l); Cotton bleu (40 mg/l); Bromocresol green (20 mg/l) and CI Reactive Red 66 (40 mg/l) dissolved in artificial seawater. The Box-Behnken design (BBD) which combine six variables with three levels each was used to determine the potential removal of dyes in ATE, by the selected microbial consortium (M31 and M69b). The experimental process indicated that decolourization of ATE reached 77.36 % under these conditions values: salinity (30 g/l), pH (9), peptone (5 g/l), inoculum size (1.5 108 CFU/ml), agitation (150 rpm) and contact time (72 h). The decolourization was confirmed by FTIR spectrum analysis of ATE before and after bacterial treatment. Bacterial strains used in this study were identified as Halomonas pacifica M31 and Shewanella algae M69b using 16 rDNA sequences. Moreover, the total genome analysis of M31 and M69b validated the implication of bacterial genes in mixture dyes removal. Therefore, the effect of the selected bacterial consortium on ATE removal was confirmed and it may be used in industrial wastewater treatment to issuing environmental safety.

[Engineering microbial consortia through synthetic biology approach].

There are a large number of natural microbial communities in nature. Different populations inside the consortia expand the performance boundary of a single microbial population through communication and division of labor, reducing the overall metabolic burden and increasing the environmental adaptability. Based on engineering principles, synthetic biology designs or modifies basic functional components, gene circuits, and chassis cells to purposefully reprogram the operational processes of the living cells, achieving rich and controllable biological functions. Introducing this engineering design principle to obtain structurally well-defined synthetic microbial communities can provide ideas for theoretical studies and shed light on versatile applications. This review discussed recent progresses on synthetic microbial consortia with regard to design principles, construction methods and applications, and prospected future perspectives.

Biofilm Formation and Genetic Diversity of Microbial Communities in Anaerobic Batch Reactor with Polylactide (PLA) Addition.

In this paper, an anaerobic digestion (AD) study was conducted on confectionery waste with granular polylactide (PLA) as a cell carrier. Digested sewage sludge (SS) served as the inoculum and buffering agent of systems. This article shows the results of the analyses of the key experimental properties of PLA, i.e., morphological characteristics of the microstructure, chemical composition and thermal stability of the biopolymer. The evaluation of quantitative and qualitative changes in the genetic diversity of bacterial communities, performed using the state-of-the-art next generation sequencing (NGS) technique, revealed that the material significantly enhanced bacterial proliferation; however, it does not change microbiome biodiversity, as also confirmed via statistical analysis. More intense microbial proliferation (compared to the control sample, without PLA and not digested, CW-control, CW-confectionery waste) may be indicative of the dual role of the biopolymer-support and medium. Actinobacteria (34.87%) were the most abundant cluster in the CW-control, while the most dominant cluster in digested samples was firmicutes: in the sample without the addition of the carrier (CW-dig.) it was 68.27%, and in the sample with the addition of the carrier (CW + PLA) it was only 26.45%, comparable to the control sample (CW-control)-19.45%. Interestingly, the number of proteobacteria decreased in the CW-dig. sample (17.47%), but increased in the CW + PLA sample (39.82%) compared to the CW-control sample (32.70%). The analysis of biofilm formation dynamics using the BioFlux microfluidic system shows a significantly faster growth of the biofilm surface area for the CW + PLA sample. This information was complemented by observations of the morphological characteristics of the microorganisms using fluorescence microscopy. The images of the CW + PLA sample showed carrier sections covered with microbial consortia.

The community-function landscape of microbial consortia.

Quantitatively linking the composition and function of microbial communities is a major aspiration of microbial ecology. Microbial community functions emerge from a complex web of molecular interactions between cells, which give rise to population-level interactions among strains and species. Incorporating this complexity into predictive models is highly challenging. Inspired by a similar problem in genetics of predicting quantitative phenotypes from genotypes, an ecological community-function (or structure-function) landscape could be defined that maps community composition and function. In this piece, we present an overview of our current understanding of these community landscapes, their uses, limitations, and open questions. We argue that exploiting the parallels between both landscapes could bring powerful predictive methodologies from evolution and genetics into ecology, providing a boost to our ability to engineer and optimize microbial consortia.

Metaproteomic and gene expression analysis of interspecies interactions in a PAH-degrading synthetic microbial consortium constructed with the key microbes of a natural consortium.

Polycyclic Aromatic Hydrocarbons (PAHs) impose adverse effects on the environment and human life. The use of synthetic microbial consortia is promising in bioremediation of contaminated sites with these pollutants. However, the design of consortia taking advantage of natural interactions has been poorly explored. In this study, a dual synthetic bacterial consortium (DSC_AB) was constructed with two key members (Sphingobium sp. AM and Burkholderia sp. Bk), of a natural PAH degrading consortium. DSC_AB showed significantly enhanced degradation of PAHs and toxic intermediary metabolites relative to the axenic cultures, indicating the existence of synergistic relationships. Metaproteomic and gene-expression analyses were applied to obtain a view of bacterial performance during phenanthrene removal. Overexpression of the Bk genes, naph, biph, tol and sal and the AM gene, ahdB, in DSC_AB relative to axenic cultures, demonstrated that both strains are actively participating in degradation, which gave evidence of cross-feeding. Several proteins related to stress response were under-expressed in DSC_AB relative to axenic cultures, indicating that the division of labour reduces cellular stress, increasing the efficiency of degradation. This is the one of the first works revealing bacterial relationships during PAH removal in a synthetic consortium applying an omics approach. Our findings could be used to develop criteria for evaluating the potential effectiveness of synthetic bacterial consortia in bioremediation.

Electrogenetic signaling and information propagation for controlling microbial consortia via programmed lysis.

To probe signal propagation and genetic actuation in microbial consortia, we have coopted the components of both redox and quorum sensing (QS) signaling into a communication network for guiding composition by "programming" cell lysis. Here, we use an electrode to generate hydrogen peroxide as a redox cue that determines consortia composition. The oxidative stress regulon of Escherichia coli, OxyR, is employed to receive and transform this signal into a QS signal that coordinates the lysis of a subpopulation of cells. We examine a suite of information transfer modalities including "monoculture" and "transmitter-receiver" models, as well as a series of genetic circuits that introduce time-delays for altering information relay, thereby expanding design space. A simple mathematical model aids in developing communication schemes that accommodate the transient nature of redox signals and the "collective" attributes of QS signals. We suggest this platform methodology will be useful in understanding and controlling synthetic microbial consortia for a variety of applications, including biomanufacturing and biocontainment.

Community succession and functional prediction of microbial consortium with straw degradation during subculture at low temperature.

To systematically explore and analyze the microbial composition and function of microbial consortium M44 with straw degradation in the process of subculture at low temperature. In this study, straw degradation characteristics of samples in different culture stages were determined. MiSeq high-throughput sequencing technology was used to analyze the evolution of community structure and its relationship with degradation characteristics of microbial consortium in different culture periods, and the PICRUSt function prediction analysis was performed. The results showed that straw degradation rate, endoglucanase activity, and filter paper enzyme activity of M44 generally decreased with increasing culture algebra. The activities of xylanase, laccase, and lignin peroxidase, as well as VFA content, showing a single-peak curve change with first an increase and then decrease. In the process of subculture, Proteobacteria, Bacteroidetes, and Firmicutes were dominant in different culture stages. Pseudomonas, Flavobacterium, Devosia, Brevundimonas, Trichococcus, Acinetobacter, Dysgonomonas, and Rhizobium were functional bacteria in different culture stages. It was found by PICRUSt function prediction that the functions were concentrated in amino acid transport and metabolism, carbohydrate transship and metabolism related genes, which may contain a large number of fibers and lignin degrading enzyme genes. In this study, the microbial community succession and the gene function in different culture periods were clarified and provide a theoretical basis for screening and rational utilization of microbial consortia.

Circuit-guided population acclimation of a synthetic microbial consortium for improved biochemical production.

Microbial consortia have been considered potential platforms for bioprocessing applications. However, the complexity in process control owing to the use of multiple strains necessitates the use of an efficient population control strategy. Herein, we report circuit-guided synthetic acclimation as a strategy to improve biochemical production by a microbial consortium. We designed a consortium comprising alginate-utilizing Vibrio sp. dhg and 3-hydroxypropionic acid (3-HP)-producing Escherichia coli strains for the direct conversion of alginate to 3-HP. We introduced a genetic circuit, named "Population guider", in the E. coli strain, which degrades ampicillin only when 3-HP is produced. In the presence of ampicillin as a selection pressure, the consortium was successfully acclimated for increased 3-HP production by 4.3-fold compared to that by a simple co-culturing consortium during a 48-h fermentation. We believe this concept is a useful strategy for the development of robust consortium-based bioprocesses.