Holistic integration of omics data reveals the drivers that shape the ecology of microbial meat spoilage scenarios.

Background: The use of omics data for monitoring the microbial flow of fresh meat products along a production line and the development of spoilage prediction tools from these data is a promising but challenging task. In this context, we produced a large multivariate dataset (over 600 samples) obtained on the production lines of two similar types of fresh meat products (poultry and raw pork sausages). We describe a full analysis of this dataset in order to decipher how the spoilage microbial ecology of these two similar products may be shaped differently depending on production parameter characteristics. Methods: Our strategy involved a holistic approach to integrate unsupervised and supervised statistical methods on multivariate data (OTU-based microbial diversity; metabolomic data of volatile organic compounds; sensory measurements; growth parameters), and a specific selection of potential uncontrolled (initial microbiota composition) or controlled (packaging type; lactate concentration) drivers. Results: Our results demonstrate that the initial microbiota, which is shown to be very different between poultry and pork sausages, has a major impact on the spoilage scenarios and on the effect that a downstream parameter such as packaging type has on the overall evolution of the microbial community. Depending on the process, we also show that specific actions on the pork meat (such as deboning and defatting) elicit specific food spoilers such as Dellaglioa algida, which becomes dominant during storage. Finally, ecological network reconstruction allowed us to map six different metabolic pathways involved in the production of volatile organic compounds involved in spoilage. We were able connect them to the different bacterial actors and to the influence of packaging type in an overall view. For instance, our results demonstrate a new role of Vibrionaceae in isopropanol production, and of Latilactobacillus fuchuensis and Lactococcus piscium in methanethiol/disylphide production. We also highlight a possible commensal behavior between Leuconostoc carnosum and Latilactobacillus curvatus around 2,3-butanediol metabolism. Conclusion: We conclude that our holistic approach combined with large-scale multi-omic data was a powerful strategy to prioritize the role of production parameters, already known in the literature, that shape the evolution and/or the implementation of different meat spoilage scenarios.

Disentangle genus microdiversity within a complex microbial community by using a multi-distance long-read binning method: example of Candidatus Accumulibacter.

Complete genomes can be recovered from metagenomes by assembling and binning DNA sequences into metagenome assembled genomes (MAGs). Yet, the presence of microdiversity can hamper the assembly and binning processes, possibly yielding chimeric, highly fragmented and incomplete genomes. Here, the metagenomes of four samples of aerobic granular sludge bioreactors containing Candidatus (Ca.) Accumulibacter, a phosphate-accumulating organism of interest for wastewater treatment, were sequenced with both PacBio and Illumina. Different strategies of genome assembly and binning were investigated, including published protocols and a binning procedure adapted to the binning of long contigs (MuLoBiSC). Multiple criteria were considered to select the best strategy for Ca. Accumulibacter, whose multiple strains in every sample represent a challenging microdiversity. In this case, the best strategy relies on long-read only assembly and a custom binning procedure including MuLoBiSC in metaWRAP. Several high-quality Ca. Accumulibacter MAGs, including a novel species, were obtained independently from different samples. Comparative genomic analysis showed that MAGs retrieved in different samples harbour genomic rearrangements in addition to accumulation of point mutations. The microdiversity of Ca. Accumulibacter, likely driven by mobile genetic elements, causes major difficulties in recovering MAGs, but it is also a hallmark of the panmictic lifestyle of these bacteria.

Time-course analysis of metabolomic and microbial responses in anaerobic digesters exposed to ammonia.

Omics longitudinal studies are effective experimental designs to inform on the stability and dynamics of microbial communities in response to perturbations, but time-course analytical frameworks are required to fully exploit the temporal information acquired in this context. In this study we investigate the influence of ammonia on the stability of anaerobic digestion (AD) microbiome with a new statistical framework. Ammonia can severely reduce AD performance. Understanding how it affects microbial communities development and the degradation progress is a key operational issue to propose more stable processes. Thirty batch digesters were set-up with different levels of ammonia. Microbial community structure and metabolomic profiles were monitored with 16 S-metabarcoding and GCMS (gas-chromatography-mass-spectrometry). Digesters were first grouped according to similar degradation performances. Within each group, time profiles of OTUs and metabolites were modelled, then clustered into similar time trajectories, evidencing for example a syntrophic interaction between Syntrophomonas and Methanoculleus that was maintained up to 387 mg FAN/L. Metabolites resulting from organic matter fermentation, such as dehydroabietic or phytanic acid, decreased with increasing ammonia levels. Our analytical framework enabled to fully account for time variability and integrate this parameter in data analysis.

Application of a path-modelling approach for deciphering causality relationships between microbiota, volatile organic compounds and off-odour profiles during meat spoilage.

Microbiological spoilage of meat is considered as a process which involves mainly bacterial metabolism leading to degradation of meat sensory qualities. Studying spoilage requires the collection of different types of experimental data encompassing microbiological, physicochemical and sensorial measurements. Within this framework, the objective herein was to carry out a multiblock path modelling workflow to decipher causality relationships between different types of spoilage-related responses: composition of microbiota, volatilome and off-odour profiles. Analyses were performed with the Path-ComDim approach on a large-scale dataset collected on fresh turkey sausages. This approach enabled to quantify the importance of causality relationships determined a priori between each type of responses as well as to identify important responses involved in spoilage, then to validate causality assumptions. Results were very promising: the data integration confirmed and quantified the causality between data blocks, exhibiting the dynamical nature of spoilage, mainly characterized by the evolution of off-odour profiles caused by the production of volatile organic compounds such as ethanol or ethyl acetate. This production was possibly associated with several bacterial species like Lactococcus piscium, Leuconostoc gelidum, Psychrobacter sp. or Latilactobacillus fuchuensis. Likewise, the production of acetoin and diacetyl in meat spoilage was highlighted. The Path-ComDim approach illustrated here with meat spoilage can be applied to other large-scale and heterogeneous datasets associated with pathway scenarios and represents a promising key tool for deciphering causality in complex biological phenomena.

Direct evidence for the role of microbial community composition in the formation of soil organic matter composition and persistence.

The largest terrestrial carbon sink on earth is soil carbon stocks. As the climate changes, the rate at which the Earth's climate warms depends in part on the persistence of soil organic carbon. Microbial turnover forms the backbone of soil organic matter (SOM) formation and it has been recently proposed that SOM molecular complexity is a key driver of stability. Despite this, the links between microbial diversity, chemical complexity and biogeochemical nature of SOM remain missing. Here we tested the hypotheses that distinct microbial communities shape the composition of SOM, and microbial-derived SOM has distinct decomposition potential depending on its community of origin. We inoculated microbial communities of varying diversities into a model soil matrix amended with simple carbon (cellobiose) and measured the thermal stability of the resultant SOM. Using a Rock-Eval® ramped thermal analysis, we found that microbial community composition drives the chemical fingerprint of soil carbon. While diversity was not a driver of SOM composition, bacteria-only communities lead to more thermally labile soil C pools than communities with bacteria and fungi. Our results provide direct evidence for a link between microbial community structure, SOM composition, and thermal stability. This evidence demonstrates the relevance of soil microorganisms in building persistent SOM stocks.

Integrating independent microbial studies to build predictive models of anaerobic digestion inhibition by ammonia and phenol.

Anaerobic digestion (AD) is a process that can efficiently degrade organic waste into renewable energies. AD failure is however common as the underpinning microbial mechanisms are highly vulnerable to a wide range of inhibitory compounds. Sequencing technologies enable the identification of microbial indicators of digesters inhibition, but existing studies are limited. They used different inocula, substrates, sites and types of reactors and reported different or contradictory indicators. Our aim was to identify a robust signature of microbial indicators of phenol and ammonia inhibitions across four independent AD microbial studies. To identify such signature, we applied an original multivariate integrative method on two in-house studies, then validated our approach by predicting the inhibitory status of samples from two other studies with more than 90% accuracy. Our approach shows how we can efficiently leverage on existing studies to extract reproducible microbial community patterns and predict AD inhibition to improve AD microbial management.

Large-scale multivariate dataset on the characterization of microbiota diversity, microbial growth dynamics, metabolic spoilage volatilome and sensorial profiles of two industrially produced meat products subjected to changes in lactate concentration and packaging atmosphere.

Data in this article provide detailed information on the diversity of bacterial communities present on 576 samples of raw pork or poultry sausages produced industrially in 2017. Bacterial growth dynamics and diversity were monitored throughout the refrigerated storage period to estimate the impact of packaging atmosphere and the use of potassium lactate as chemical preservative. The data include several types of analysis aiming at providing a comprehensive microbial ecology of spoilage during storage and how the process parameters do influence this phenomenon. The analysis includes: the gas content in packaging, pH, chromametric measurements, plate counts (total mesophilic aerobic flora and lactic acid bacteria), sensorial properties of the products, meta-metabolomic quantification of volatile organic compounds and bacterial community metagenetic analysis. Bacterial diversity was monitored using two types of amplicon sequencing (16S rRNA and GyrB encoding genes) at different time points for the different conditions (576 samples for gyrB and 436 samples for 16S rDNA). Sequencing data were generated by using Illumina MiSeq. The sequencing data have been deposited in the bioproject PRJNA522361. Samples accession numbers vary from SAMN10964863 to SAMN10965438 for gyrB amplicon and from SAMN10970131 to SAMN10970566 for 16S.

Tile Drainage as a Hydrologic Pathway for Phosphorus Export from an Agricultural Subwatershed.

Cyanobacteria growth in Missisquoi Bay of Lake Champlain is triggered by the P load carried by tributaries in surrounding watersheds where agriculture is a dominant land use. The objective of this study was to apportion the total P (TP) load in streamflow from an agricultural subwatershed into distinct hydrologic pathways: groundwater resurgence, surface runoff, and tile drainage components (matrix flow and preferential flow). Stream discharge during peak flow was separated into these four components using electrical conductivity (EC)-discharge relationships developed from the stream water EC at the subwatershed outlet and from EC values of surface runoff and tile drain water in 10 fields within the subwatershed. The four-component hydrograph model revealed that 46 to 67% of the TP load at the outlet originated from surface runoff during peak flow. Preferential flow was responsible for most of the particulate P and dissolved reactive P loads lost through tile drainage. Groundwater resurgence was a minor source of TP, whereas other sources such as streambank erosion and resuspended sediments contributed up to 21% of the TP load and from 36 to 41% of the particulate P load at the subwatershed outlet. This work confirms that tile drainage contributes to the TP load in agricultural subwatersheds in the Missisquoi Bay region.

Detection of an amplification bias associated to Leuconostocaceae family with a universal primer routinely used for monitoring microbial community structures within food products.

OBJECTIVES: Sequencing of 16S rDNA V3-V4 region is widely applied for food community profiling. However, two different universal forward primers (named here MUYZER-primer1 and KLINDWORTH-primer2) targeting an identical conservative sequence upstream of the V3 region of 16S rRNA gene, and only distinguished by a single mismatch are both used. This study was carried out to compare whether the accuracy of food microbiota analysis would depend on the choice of one of these two primers. RESULTS: Alignment of both primers with common food-borne bacteria 16S sequences revealed that the mismatch between both primers might specifically affect the amplification of Leuconostoc, Oenococcus and Fructobacillus species but not Weissella species. Food products containing either Leuconostoc and/or Weissella were selected for a detection test. As expected from our in silico analysis, our study showed that this mismatch induced a strong biased amplification specifically associated to the OTUs belonging to the genus Leuconostoc but not to the genus Weissella. In presence of Muyzer-primer1, none of the sequences expected for Leuconostoc genus was detected whereas those sequences were correctly amplified with Klindworth-primer2. Since Leuconostoc is an important genus in food, agro-environments and in digestive tract of animals, we recommend that Muyzer-primer1 should thus be abandoned for the bacterial characterization of their associated microbiota.

Inhibition of anaerobic digestion by phenol and ammonia: Effect on degradation performances and microbial dynamics.

Data in this article provide detailed information on the microbial dynamics during inhibition of anaerobic digestion by phenol and ammonia. Ten concentrations of both inhibitors were tested in triplicates. Data include the operational conditions and degradation performance measurements, as well as microbial community analysis, by 16S rRNA gene sequencing, at different time points for the different conditions (96 samples). Sequencing data were generated by using IonTorrent PGM sequencer. This data is associated with the research articles "Community shifts within anaerobic digestion microbiota facing phenol inhibition: Towards early warning microbial indicators?" (Poirier et al., 2016a) [1] and "Anaerobic digestion of biowaste under extreme ammonia concentration: Identification of key microbial phylotypes" (Poirier et al., 2016b) [2]. The sequencing data have been deposited in the bioproject PRJNA450311, with the dataset identifier (TaxID) 1263854. Samples accession numbers go from SAMN08934853 to SAMN08934947.

Influence of support media supplementation to reduce the inhibition of anaerobic digestion by phenol and ammonia: Effect on degradation performances and microbial dynamics.

Data in this article provide detailed information on the microbial dynamics within digesters supplemented with different support media (two types of zeolites, two types of activated carbons, one type of chitosan, one control) in presence of different inhibitory conditions (control without inhibitor, 1.3 g/L of phenol and 19 g/L of total ammonia nitrogen). Data include the operational conditions and degradation performance measurements, as well as microbial community analysis, by 16S rRNA gene sequencing, at different time points for the different conditions (samples). Sequencing data were generated by using IonTorrent PGM sequencer. This data is associated with the research articles "Improving anaerobic digestion with support media: Mitigation of ammonia inhibition and effect on microbial communities?" (Poirier et al., 2017) [1] and "Support media can steer methanogenesis in presence of phenol through biotic and abiotic effects" (Poirier et al., 2018) [2]. The sequencing data have been deposited with links to BioProject accession number PRJNA450513, in the NCBI BioProject database (https://www.ncbi.nlm.nih.gov/sra/?term=PRJNA450513). Samples accession numbers go from SAMN08940368 to SAMN08940426.

Deciphering intra-species bacterial diversity of meat and seafood spoilage microbiota using gyrB amplicon sequencing: A comparative analysis with 16S rDNA V3-V4 amplicon sequencing.

Meat and seafood spoilage ecosystems harbor extensive bacterial genomic diversity that is mainly found within a small number of species but within a large number of strains with different spoilage metabolic potential. To decipher the intraspecies diversity of such microbiota, traditional metagenetic analysis using the 16S rRNA gene is inadequate. We therefore assessed the potential benefit of an alternative genetic marker, gyrB, which encodes the subunit B of DNA gyrase, a type II DNA topoisomerase. A comparison between 16S rDNA-based (V3-V4) amplicon sequencing and gyrB-based amplicon sequencing was carried out in five types of meat and seafood products, with five mock communities serving as quality controls. Our results revealed that bacterial richness in these mock communities and food samples was estimated with higher accuracy using gyrB than using16S rDNA. However, for Firmicutes species, 35% of putative gyrB reads were actually identified as sequences of a gyrB paralog, parE, which encodes subunit B of topoisomerase IV; we therefore constructed a reference database of published sequences of both gyrB and pare for use in all subsequent analyses. Despite this co-amplification, the deviation between relative sequencing quantification and absolute qPCR quantification was comparable to that observed for 16S rDNA for all the tested species. This confirms that gyrB can be used successfully alongside 16S rDNA to determine the species composition (richness and evenness) of food microbiota. The major benefit of gyrB sequencing is its potential for improving taxonomic assignment and for further investigating OTU richness at the subspecies level, thus allowing more accurate discrimination of samples. Indeed, 80% of the reads of the 16S rDNA dataset were represented by thirteen 16S rDNA-based OTUs that could not be assigned at the species-level. Instead, these same clades corresponded to 44 gyrB-based OTUs, which differentiated various lineages down to the subspecies level. The increased ability of gyrB-based analyses to track and trace phylogenetically different groups of strains will generate improved resolution and more reliable results for studies of the strains implicated in food processes.

Draft Genome Sequences of Nine Strains of Brochothrix thermosphacta, Carnobacterium divergens, Lactobacillus algidus, Lactobacillus fuchuensis, Lactococcus piscium, Leuconostoc gelidum subsp. gasicomitatum, Pseudomonas lundensis, and Weissella viridescens, a Collection of Psychrotrophic Species Involved in Meat and Seafood Spoilage.

In this study, we present the draft genome sequences of nine strains from various psychrotrophic species identified in meat products and being recognized as important emerging food spoilers. Many of these species have only one or few strains being sequenced, and this work will contribute to the improvement of the overall genomic knowledge about them.

Support media can steer methanogenesis in the presence of phenol through biotic and abiotic effects.

A wide variety of inhibitors can induce anaerobic digester disruption. To avoid performance losses, support media can be used to mitigate inhibitions. However, distinguishing the physico-chemical from the biological mechanisms of such strategies remains delicate. In this framework, the impact of 10  g/L of different types of zeolites and activated carbons (AC) on microbial community dynamics during anaerobic digestion of biowaste in the presence of 1.3 g/L of phenol was evaluated with 16 S rRNA gene sequencing. In the presence of AC, methanogenesis inhibition was rapidly removed due to a decrease of phenol concentration. This abiotic effect related to the physico-chemical properties of AC led to increased final CH4 and CO2 productions by 29-31% compared to digesters incubated without support. Interestingly, although zeolite did not adsorb phenol, final CH4 and CO2 production reached comparable levels as with AC. Nevertheless, compared to digesters incubated without support, methanogenesis lag phase duration was less reduced in the presence of zeolites (5 ±â€¯1 days) than in the presence of activated carbons (12 ±â€¯2 days). Both types of support induced biotic effects. AC and zeolite both allowed the preservation of the major representative archaeal genus of the non-inhibited ecosystem, Methanosarcina. By contrast, they distinctly shaped bacterial populations. OTUs belonging to class W5 became dominant at the expense of OTUs assigned to orders Clostridiales, Bacteroidales and Anaerolinales in the presence of AC. Zeolite enhanced the implantation of OTUs assigned to bacterial phylum Cloacimonetes. This study highlighted that supports can induce biotic and abiotic effects within digesters inhibited with phenol, showing potentialities to enhance anaerobic digestion stability under disrupting conditions.

Improving anaerobic digestion with support media: Mitigation of ammonia inhibition and effect on microbial communities.

This study aimed at providing a better understanding of the influence of support media (10g/L of zeolites, 10g/L of activated carbons, and 1g/L of chitosan) on key phylotypes steering anaerobic digestion (AD) performance in presence of 19g/L of Total Ammonia Nitrogen (TAN) within batch digesters. Support media did not influence TAN concentration. However, both zeolites and activated carbon 1 reduced methanization lag phase by 47% and 25%, respectively. By contrast, activated carbon 2 and chitosan led to an increase of methanization lag phase by 51% and 32%, respectively. 16S rRNA gene sequencing revealed that zeolites preserved Methanosarcina and enhanced Methanobacterium. In presence of activated carbon 1, Methanoculleus, became predominant earlier than without support while chitosan and activated carbon 2 limited its implantation. This study highlighted potentialities to use supports to enhance AD stability under extreme TAN concentration and evidenced their specific influence on the microbiota composition.

Community shifts within anaerobic digestion microbiota facing phenol inhibition: Towards early warning microbial indicators?

Performance stability is a key operational issue for anaerobic digestion (AD) and phenolic compounds are regularly mentioned as a major cause of digester failures. To get more insights into AD microbiota response to a wide range of inhibition levels, anaerobic batch toxicity assays were conducted with ten phenol concentrations up to 5.00 g/L. Final AD performance was not impaired up to 1.00 g/L. However, progressive shifts in microbial community structure were detected from 0.50 g/L. The methanogenic function was maintained along with increasing initial phenol concentrations up to 2.00 g/L thanks to the emergence of genus Methanoculleus at the expense of Methanosarcina. Within syntrophic populations, family Syntrophomonadaceae proportion was gradually reduced by phenol while Synergistaceae gained in importance in the microbiome. Moreover, at 2.00 g/L, the relative abundance of families belonging to order Clostridiales dropped, leading to the predominance of populations assigned to order Bacteroidales even though it did not prevent final AD performance deterioration. It illustrates the high level of adaptability of archaeal and bacterial communities and suggests the possibility of determining early warning microbial indicators associated with phenol inhibition.

Acclimation strategy to increase phenol tolerance of an anaerobic microbiota.

A wide variety of inhibitory substances can induce anaerobic digester upset or failure. In this work the possibility to improve the resistance of an anaerobic microbiota to a common pollutant, the phenol, was evaluated in a lab-scale semi-continuous bioreactor. An acclimation strategy, consisting in a regular step-wise adaptation of the microbiota to stressful condition was employed. Degradation performances were monitored and molecular tools (16S sequencing and ARISA fingerprinting technique) were used to track changes in the microbial community. The acclimation strategy progressively minimized the effect of phenol on degradation performances. After 3 successive disturbance episodes, microbiota resistance was considerably developed and total inhibition threshold increased from 895 to 1942mg/L of phenol. Microbiota adaptation was characterized by the selection of the most resistant Archaea OTU from Methanobacterium genus and an important elasticity of Bacteria, especially within Clostridiales and Bacteroidales orders, that probably enabled the adaptation to more and more stressful conditions.

Anaerobic digestion of biowaste under extreme ammonia concentration: Identification of key microbial phylotypes.

Ammonia inhibition represents a major operational issue for anaerobic digestion (AD). In order to get more insights into AD microbiota resistance, anaerobic batch reactors performances were investigated under a wide range of Total Ammonia Nitrogen (TAN) concentrations up to 50.0g/L at 35°C. The half maximal inhibitory concentration (IC50) value was determined to be 19.0g/L. Microbial community dynamics revealed that above a TAN concentration of 10.0g/L, remarkable modifications within archaeal and bacterial communities occurred. 16S rRNA gene sequencing analysis showed a gradual methanogenic shift between two OTUs from genus Methanosarcina when TAN concentration increased up to 25.0g/L. Proportion of potential syntrophic microorganisms such as Methanoculleus and Treponema progressively raised with increasing TAN up to 10.0 and 25.0g/L respectively, while Syntrophomonas and Ruminococcus groups declined. In 25.0g/L assays, Caldicoprobacter were dominant. This study highlights the emergence of AD key phylotypes at extreme ammonia concentrations.

Schizophrenia patients with polydipsia and water intoxication are characterized by greater severity of psychotic illness and a more frequent history of alcohol abuse.

Polydipsia and water intoxication (PWI) are relatively frequent among schizophrenic subjects, particularly in institutional settings and may lead to severe complications. However, little is known on their association with other characteristics of psychosis. Hence, we took advantage of a cohort of 114 subjects extensively assessed on natural history and clinical variables to examine the correlates of PWI in chronic schizophrenia. We randomly sampled DSM-IV schizophrenic subjects from: i) a lower functioning subgroup, i.e., long-term psychiatric wards or highly structured group housing facilities; and ii) a higher functioning subgroup, i.e., patients living in the community without supervision. Subjects were assessed from multiple sources for lifetime severity of positive, disorganisation, negative and depressive symptoms, premorbid adjustment, age of onset, level of functioning, comorbid diagnoses of substance abuse and lifetime history of PWI. Twelve subjects (10.5%) met our PWI criteria. We observed more severe psychotic symptoms, earlier onset, poorer current adjustment and more frequent prior alcohol use disorder in PWI subjects. When restricting comparisons to patients living in institutional setting, differences on clinical and natural history variables vanished but the association between PWI and prior alcohol abuse persisted (72.7% in PWI vs. 21.4% in non-PWI subjects, p<0.01). Onset of alcohol abuse predated the onset of PWI by a mean of 12.8 years. PWI schizophrenic subjects are characterized by a non-specific greater severity on a broad array of clinical and natural history variables and by a specific association with prior alcohol abuse. Thus, our data suggest that a greater severity of illness and a prior history of alcohol use disorders interact in increasing the risk of developing PWI in chronic schizophrenic patients.

A factor analysis of the Strauss and Carpenter revised outcome criteria scale: a validation of the French translation.

This article seeks to validate the French translation of the Strauss and Carpenter revised outcome criteria scale (SCOCS-R) through the study of its interrater reliability, its convergent validity, and its factor structure. Using a sample of 113 DSM-IV schizophrenic subjects, we assessed the interrater reliability of the SCOCS-R and its convergent validity with an already validated scale (Social and Occupational Functioning Assessment Scale). The factor structure of the SCOCS-R was assessed using a principal components analysis. Interrater reliability was excellent (ri > or = 0.88 for each of the individual items), and the convergent validity with the Social and Occupational Functioning Assessment Scale proved to be highly satisfactory (r = 0.89; p < .0001). Factor analyses yielded two factors corresponding to social functioning and professional functioning. These factors accounted for 78% of the variance of outcome. These results demonstrate the reliability and the validity of the French translation of the SCOCS-R. Moreover, the two dimensions yielded by our factor analysis add to the evidence of the multidimensional structure of outcome. This article supports the relevance of the SCOCS-R to assess the dimensions of outcome in schizophrenic subjects.