An in-depth evaluation of metagenomic classifiers for soil microbiomes

BACKGROUND

Recent endeavours in metagenomics, exemplified by projects such as the human microbiome project and TARA Oceans, have illuminated the complexities of microbial biomes. A robust bioinformatic pipeline and meticulous evaluation of their methodology have contributed to the success of these projects. The soil environment, however, with its unique challenges, requires a specialized methodological exploration to maximize microbial insights. A notable limitation in soil microbiome studies is the dearth of soil-specific reference databases available to classifiers that emulate the complexity of soil communities. There is also a lack of in-vitro mock communities derived from soil strains that can be assessed for taxonomic classification accuracy.

RESULTS

In this study, we generated a custom in-silico mock community containing microbial genomes commonly observed in the soil microbiome. Using this mock community, we simulated shotgun sequencing data to evaluate the performance of three leading metagenomic classifiers: Kraken2 (supplemented with Bracken, using a custom database derived from GTDB-TK genomes along with its own default database), Kaiju, and MetaPhlAn, utilizing their respective default databases for a robust analysis. Our results highlight the importance of optimizing taxonomic classification parameters, database selection, as well as analysing trimmed reads and contigs. Our study showed that classifiers tailored to the specific taxa present in our samples led to fewer errors compared to broader databases including microbial eukaryotes, protozoa, or human genomes, highlighting the effectiveness of targeted taxonomic classification. Notably, an optimal classifier performance was achieved when applying a relative abundance threshold of 0.001% or 0.005%. The Kraken2 supplemented with bracken, with a custom database demonstrated superior precision, sensitivity, F1 score, and overall sequence classification. Using a custom database, this classifier classified 99% of in-silico reads and 58% of real-world soil shotgun reads, with the latter identifying previously overlooked phyla using a custom database.

CONCLUSION

This study underscores the potential advantages of in-silico methodological optimization in metagenomic analyses, especially when deciphering the complexities of soil microbiomes. We demonstrate that the choice of classifier and database significantly impacts microbial taxonomic profiling. Our findings suggest that employing Kraken2 with Bracken, coupled with a custom database of GTDB-TK genomes and fungal genomes at a relative abundance threshold of 0.001% provides optimal accuracy in soil shotgun metagenome analysis.

A pilot randomized controlled trial evaluating outdoor community walking for knee osteoarthritis: walk

OBJECTIVES

To determine the feasibility of a randomized controlled trial (RCT) examining outdoor walking on knee osteoarthritis (KOA) clinical outcomes and magnetic resonance imaging (MRI) structural changes.

METHOD

This was a 24-week parallel two-arm pilot RCT in Tasmania, Australia. KOA participants were randomized to either a walking plus usual care group or a usual care control group. The walking group trained 3 days/week. The primary outcome was feasibility assessed by changes being required to the study design, recruitment, randomization, program adherence, safety, and retention. Exploratory outcomes were changes in symptoms, physical performance/activity, and MRI measures.

RESULTS

Forty participants (mean age 66 years (SD 1.4) and 60% female) were randomized to walking (n = 24) or usual care (n = 16). Simple randomization resulted in a difference in numbers randomized to the two groups. During the study, class sizes were reduced from 10 to 8 participants to improve supervision, and exclusion criteria were added to facilitate program adherence. In the walking group, total program adherence was 70.0% and retention 70.8% at 24 weeks. The walking group had a higher number of mild adverse events and experienced clinically important improvements in symptoms (e.g., visual analogue scale (VAS) knee pain change in the walking group: - 38.7 mm [95% CI - 47.1 to - 30.3] versus usual care group: 4.3 mm [- 4.9 to 13.4]).

CONCLUSIONS

This study supports the feasibility of a full-scale RCT given acceptable adherence, retention, randomization, and safety, and recruitment challenges have been identified. Large symptomatic benefits support the clinical usefulness of a subsequent trial.

TRIAL REGISTRATION NUMBER

12618001097235. Key Points • This pilot study is the first to investigate the effects of an outdoor walking program on knee osteoarthritis clinical outcomes and MRI joint structure, and it indicates that a full-scale RCT is feasible. • The outdoor walking program (plus usual care) resulted in large improvements in self-reported knee osteoarthritis symptoms compared to usual care alone. • The study identified recruitment challenges, and the manuscript explores these in more details and provides recommendations for future studies.

Impacts of metal stress on extracellular microbial products, and potential for selective metal recovery

Harnessing microbial capabilities for metal recovery from secondary waste sources is an eco-friendly and sustainable approach for the management of metal-containing wastes. Soluble microbial products (SMP) and extracellular polymeric substances (EPS) are the two main groups of extracellular compounds produced by microorganisms in response to metal stress that are of great importance for remediation and recovery of metals. These include various high-, and low, molecular weight components, which serve various functional and structural roles. These compounds often contain functional groups with metal binding potential that can attenuate metal stress by sequestering metal ions, making them less bioavailable. Microorganisms can regulate the content and composition of EPS and SMP in response to metal stress in order to increase the compounds specificity and capacity for metal binding. Thus, EPS and SMP represent ideal candidates for developing technologies for selective metal recovery from complex wastes. To discover highly metal-sorptive compounds with specific metal binding affinity for metal recovery applications, it is necessary to investigate the metal binding affinity of these compounds, especially under metal stressed conditions. In this review we critically reviewed microbial EPS and SMP production as a response to metal stress with a particular emphasis on the metal binding properties of these compounds and their role in altering metal bioavailability. Furthermore, for the first time, we compiled the available data on potential application of these compounds for selective metal recovery from waste streams.

Critical evaluation of the use of artificial data for machine learning based de novo peptide identification

Proteins are essential components of all living cells and so the study of their in situ expression, proteomics, has wide reaching applications. Peptide identification in proteomics typically relies on matching high resolution tandem mass spectra to a protein database but can also be performed de novo. While artificial spectra have been successfully incorporated into database search pipelines to increase peptide identification rates, little work has been done to investigate the utility of artificial spectra in the context of de novo peptide identification. Here, we perform a critical analysis of the use of artificial data for the training and evaluation of de novo peptide identification algorithms. First, we classify the different fragment ion types present in real spectra and then estimate the number of spurious matches using random peptides. We then categorise the different types of noise present in real spectra. Finally, we transfer this knowledge to artificial data and test the performance of a state-of-the-art de novo peptide identification algorithm trained using artificial spectra with and without relevant noise addition. Noise supplementation increased artificial training data performance from 30% to 77% of real training data peptide recall. While real data performance was not fully replicated, this work provides the first steps towards an artificial spectrum framework for the training and evaluation of de novo peptide identification algorithms. Further enhanced artificial spectra may allow for more in depth analysis of de novo algorithms as well as alleviating the reliance on database searches for training data.

Application of a Novel Hybrid CNN-GNN for Peptide Ion Encoding

Almost all state-of-the-art de novo peptide sequencing algorithms now use machine learning models to encode fragment peaks and hence identify amino acids in mass spectrometry (MS) spectra. Previous work has highlighted how the inherent MS challenges of noise and missing peptide peaks detrimentally affect the performance of these models. In the present research we extracted and evaluated the encoding modules from 3 state-of-the-art de novo peptide sequencing algorithms. We also propose a convolutional neural network-graph neural network machine learning model for encoding peptide ions in tandem MS spectra. We compared the proposed encoding module to those used in the state-of-the-art de novo peptide sequencing algorithms by assessing their ability to identify b-ions and y-ions in MS spectra. This included a comprehensive evaluation in both real and artificial data across various levels of noise and missing peptide peaks. The proposed model performed best across all data sets using two different metrics (area under the receiver operating characteristic curve (AUC) and average precision). The work also highlighted the effect of including additional features such as intensity rank in these encoding modules as well as issues with using the AUC as a metric. This work is of significance to those designing future de novo peptide identification algorithms as it is the first step toward a new approach.

AB0994 Exploring knee osteoarthritis pain trajectories and movement-evoked pain changes during a 24-week outdoor walking program (WALK)

Background

Exercise therapy is recommended as first line treatment for knee osteoarthritis (OA), but it remains to be sub-optimally applied (1). Movement-evoked pain is a potential barrier to exercise adherence, but recent evidence suggests that such pain can be improved by training (2). Walking programs are low-cost, easily adopted and can be performed outdoors which can minimize the risk of SARS-CoV-2 transmission when in a group (3).

Objectives

To explore the acute pain trajectories of individuals with knee OA during a 24-week outdoor walking intervention. In addition, to explore the effect of pain trajectories and/or baseline characteristics on retention and adherence.

Methods

Individuals with clinical knee OA and bone marrow lesions (BMLs) on magnetic resonance imaging (MRI) were asked to follow a 24-week walking program. Every week consisted of two one hour supervised group sessions at various outdoor locations and one unsupervised session. At the start and end of every supervised group walk, knee pain was self-reported by participants to their trainer using a numerical rating scale (NRS) (0-10). The difference between the NRS pain values was considered as an acute pain change evoked by that walk. At baseline, the most affected knee of each participant was assessed using the Visual Analogue Scale (VAS) pain, the Western Ontario and McMasters Universities Osteoarthritis Index (WOMAC) pain, stiffness and function, wellbeing (3 questionnaires) and the Osteoarthritis Research Society International (OARSI) recommended strength and performance measures.

Results

In total, N = 24 participants started the program of whom N = 7 (29%) withdrew. Pain at the start of each walk decreased from NRS 2.5 (SD 1.6) at the first walk (N = 24) to NRS 0.9 (SD 0.8) at the final walk (N = 17). This pain was estimated to decrease on NRS by -0.04 (95% CI -0.05 to -0.02) per supervised session, p < 0.001 during the first 12 weeks and -0.01 (95% CI -0.02 to -0.004), p = 0.004 during the second twelve weeks of the program. The number (%) of participants who experienced an acute increase in pain decreased from 11 (45.8%) at the first walk to 4 (23.5%) at the last walk.

At baseline, non-adherent participants (<70% of group sessions) (N = 11) had lower physical performance scores, including the 30s Chair Stand Test (mean 10 (SD 1.7) stands versus mean 12.0 (SD 1.7) stands, p = 0.011), Fast Past Walk Test (1.23 (SD 0.14) meter per seconds (m/s) vs 1.50 (SD 0.20) m/s, p = 0.001), Six Minute Walk Test (418.8 (SD 75.9) m vs 529 (SD 72.6) m, p = 0.002), compared to adherent participants (N = 13). Non-adherent participants also had less severe self-reported symptoms including WOMAC stiffness (90.7 (SD 44.5) mm vs 121.5 (SD 17.0) mm, p = 0.031), compared to adherent participants. During the first two weeks of walking, acute increases in pain on average (mean ≥0.5 NRS) were reported by a greater number of non-adherent (N = 5 (45.5%)) than adherent participants (n = 4 (30.8%)).

Conclusion

This was an exploratory study and results need to be interpreted with caution due to the small sample size. The walking program resulted in clinically important improvements (MCIIs) (≥ 1 on NRS) (4) in start pain and acute pain changes. Improvements in start pain during the first 12-weeks were comparable to improvements measured in the NEMEX program (2) and may suggest that 12 weeks of exercise is sufficient to achieve MCIIs in pain. Improvements in acute changes in pain were smaller, which may have been related to a floor effect (5). Lower physical performance scores at baseline and more acute increases in pain during the first two weeks was associated with non-adherence. Participants with these characteristics may benefit from a lighter introduction to exercise.

References

[1]Bennell KL, et al. The Lancet Regional Health-Western Pacific. 2021;12:100187.

[2]Sandal LF, et al. Osteoarthritis and cartilage. 2016;24(4):589-92.

[3]Bulfone TC, et al. The Journal of infectious diseases. 2021;223(4):550-61.

[4]Perrot S, et al. Pain. 2013;154(2):248-56.

[5]McHorney CA, et al. Quality of life research. 1995;4(4):293-307.

Acknowledgements

We thank the participants who made this study possible. We would like to acknowledge the research staff, Kate Probert, Lizzy Reid, Simone Fitzgerald, Claire Roberts, Jasmin Ritchie, Dawn Simpson, and Tim Albion. We also thank Hamish Newsham-West for his contribution to the study design.

Disclosure of Interests

Stan Drummen: None declared, Saliu Balogun: None declared, Lieke Scheepers Grant/research support from: Competitive Grant Program Inflammation ASPIRE 2020 Rheumatology International Developed Markets from Pfizer, Employee of: previously worked as an Associate Director Epidemiology at the Medical Evidence Observational Research Department at AstraZeneca., Ishanka Munugoda: None declared, aroub lahham: None declared, Kim Bennell: None declared, Rana Hinman: None declared, Michele Callisaya: None declared, Guoqi Cai: None declared, Petr Otahal: None declared, Tania Winzenberg Consultant of: received payment to create educational material by AMGEN, Zhiqiang Wang: None declared, Benny Antony: None declared, Johanne Martel-Pelletier Shareholder of: ArthroLab Inc., Jean-Pierre Pelletier Shareholder of: ArthroLab Inc., François Abram Consultant of: ArthroLab Inc., Employee of: Arthrolab Inc., Graeme Jones Speakers bureau: received payment for a speakers bureau from Novartis, Dawn Aitken: None declared

POS0231 GENETIC BIOMARKERS, SNP GENES AND mtDNA HAPLOGROUPS, PREDICT OSTEOARTHRITIS STRUCTURAL PROGRESSORS THROUGH THE USE OF SUPERVISED MACHINE LEARNING

Background

Knee osteoarthritis is the most prevalent chronic musculoskeletal debilitating disease. Current treatments are only symptomatic and to improve this, we need a robust prediction model to stratify patients at an early stage according to the risk of joint structure disease progression. Some genetic factors, including single nucleotide polymorphism (SNP) genes and mitochondrial (mt)DNA haplogroups/clusters, have been linked to this disease.

Objectives

For the first time, we aim to determine, by using machine learning, whether some SNP genes and mtDNA haplogroups/clusters alone or combined could predict early knee osteoarthritis structural progressors.

Methods

Participants (901) were first classified for the probability of being structural progressors. Genotyping included SNP genes TP63, FTO, GNL3, DUS4L, GDF5, SUPT3H, MCF2L, TGFA, mtDNA haplogroups H, J, T, Uk, others, and clusters HV, TJ, KU, C-others. They were considered for prediction with major risk factors of osteoarthritis, namely, age and body mass index (BMI). Seven supervised machine learning methodologies were evaluated. The support vector machine was used to generate gender-based models. The best input combination was assessed using sensitivity and synergy analyses. Validation was performed using 10-fold cross-validation as well as an external cohort (TASOAC).

Results

From 277 models, two were defined. Both used age and BMI in addition for the first one of the SNP genes TP63, DUS4L, GDF5, FTO with an accuracy of 85.0%; the second profits from the association of mtDNA haplogroups and SNP genes FTO and SUPT3H with 82.5% accuracy. The highest impact was associated with the haplogroup H, the presence of CT alleles for rs8044769 at FTO, and the absence of AA for rs10948172 at SUPT3H. Validation accuracy with the cross-validation (about 95%) and the external cohort (90.5%, 85.7%, respectively) was excellent for both models.

Conclusion

This study introduces a novel source of decision support in precision medicine in which, for the first time, two models were developed consisting of i) age, BMI, TP63, DUS4L, GDF5, FTO and ii) the optimum one as it has one less variable: age, BMI, mtDNA haplogroup, FTO, SUPT3H. Such a framework is translational and would be of benefit to patients at risk of structural progressive knee osteoarthritis.

Acknowledgements

The authors would like to thank the Osteoarthritis Initiative (OAI) participants and Coordinating Center for their work in generating the clinical and radiological data of the OAI cohort and for making them publicly available. The OAI is a public-private partnership comprised of five contracts (N01-AR-2-2258; N01-AR-2-2259; N01-AR-2-2260; N01-AR-2-2261; N01-AR-2-2262) funded by the National Institutes of Health, a branch of the Department of Health and Human Services, and conducted by the OAI Study Investigators. Private funding partners include Merck Research Laboratories; Novartis Pharmaceuticals Corporation, GlaxoSmithKline; and Pfizer, Inc. Private sector funding for the OAI is managed by the Foundation for the National Institutes of Health. This manuscript was prepared using an OAI public use data set and does not necessarily reflect the opinions or views of the OAI investigators, the NIH, or the private funding partners. None of the authors are part of the OAI investigator team. Moreover, the authors are also grateful to the TASOAC participants.

A special thanks to ArthroLab Inc. for having provided the MRI data used for classifying structural progressors for each individual.

Disclosure of Interests

Hossein Bonakdari: None declared, Jean-Pierre Pelletier Shareholder of: ArthroLab Inc., Grant/research support from: Work supported in part by the Osteoarthritis Research Unit of the University of Montreal Hospital Research Centre and the Chair in Osteoarthritis from the University of Montreal., Francisco J. Blanco: None declared, Ignacio Rego-Perez: None declared, Alejandro Durán-Sotuela: None declared, Dawn Aitken: None declared, Graeme Jones: None declared, Flavia Cicuttini: None declared, Afshin Jamshidi Grant/research support from: Received a bursary from the Canada First Research Excellence Fund through the TransMedTech Institute in Canada., François Abram Employee of: was an employee of ArthroLab Inc., Johanne Martel-Pelletier Shareholder of: ArthroLab Inc., Grant/research support from: Work supported in part by the Osteoarthritis Research Unit of the University of Montreal Hospital Research Centre and the Chair in Osteoarthritis from the University of Montreal.

Perfluorooctanoic acid (PFOA) sensitises E. coli to acid stress

Per-and Polyfluoroalkyl Substances (PFAS), which includes PFOS and PFOA, are recognized as the most important class of emerging contaminants due to their widespread presence in wildlife and humans, their environmental persistence, bioaccumulative potential, and toxicity. Low environmental pH conditions affect the state and physicochemical properties of PFAS, which in turn impacts on their toxicity. Sparse information is available regarding the effect of these compounds on microorganisms, and the possible associated knock-on effect on ecosystem services. The purpose of this study is to investigate the ability of E. coli to tolerate stress in the presence of PFAS compounds. To this end, we carried out phenotypic comparisons of E. coli exposed to a series of environmental conditions in the presence and absence of PFOA and PFOS. Quite remarkably, E. coli growth was not affected by the presence of PFOA and PFOS up to 500 mg/L. The survival of E. coli at pH3, however, decreased by more than three-fold when the medium was supplemented with PFOA. PFOA and PFOS were also found to decrease the growth rates of E. coli in minimal media in the presence of 0.75 and 1M NaCl. We are currently screening further stresses of environmental relevance with the aim to conduct molecular investigations to examine the mechanisms underpinning the effect of PFAS exposure on bacterial stress tolerance. This work will provide some insights into the impact of PFAS on microorganisms, which should shed new light on the assessment of the ecological effects of PFAS.

The Survival of Salmonella Senftenberg, Escherichia coli O157:H7, Listeria monocytogenes, Enterococcus faecalis and Clostridium sporogenes in Sandy and Clay Loam Textured Soils When Applied in Bovine Slurry or Unpasteurised Digestate and the Run-Off Rate for a Test Bacterium, Listeria innocua, When Applied to Grass in Slurry and Digestate

This study investigated the survival of Salmonella Senftenberg, Escherichia coli O157:H7, Listeria monocytogenes, Enterococcus faecalis and Clostridium sporogenes in sandy and clay loam textured soils when applied in bovine slurry or unpasteurised digestate, using laboratory based inoculation studies. The run-off rate for a test bacterium, Listeria innocua, when applied to grass in slurry and digestate, was also examined using field studies. Bovine slurry and digestate were inoculated with the target bacteria to a final concentration of 106 log10 cfu/g or spores/g, thoroughly mixed into soil samples and incubated at 4°C or 14°C. Samples were removed periodically and the surviving cells enumerated using AOAC or equivalent methods. The loss of viability/culturability phase followed first order kinetics and T90 values ranged from 11.9 to 166.7 d at 4°C and from 6.0 to 156 d at 14°C. With the exception of E. coli O157:H7 and E. faecalis in sandy loam textured soil at 14°C (T90 values were significantly (P &lt; 0.05) higher in slurry) the type of soil texture or application material (slurry or digestate) did not affect survival rates. In the field study, 12 grass covered micro-plots were prepared. L. innocua was applied in digestate and bovine slurry and rainfall was simulated at a target rate of ~11 mm per plot per h−1. Rainfall simulation (30 min) took place after 24, 48 h, 14 d and 30 d. Run-off samples were tested for the L. innocua strain using Brilliance Listeria agar supplemented with streptomycin sulphate (1,000 μg/ml) at 37°C for 48 h, as were soil samples after 30, 58, 86 and 112 d. Significantly (P &lt; 0.05) lower counts were obtained in the run-off from digestate after 1, 2 and 30 d as compared to slurry. It was concluded that the type of organic fertiliser does not affect the bacterial survival rates in sandy and clay soils, with the exception of E. coli O157:H7 and E. faecalis in sandy loam textured soil at 14°C. Furthermore, bacteria may be retained better in the soil-digestate matrices during rainfall although additional research is required to further validate and provide the scientific basis for this observation.

Evolutionary trade-offs between growth and survival: The delicate balance between reproductive success and longevity in bacteria

All living cells strive to allocate cellular resources in a way that promotes maximal evolutionary fitness. While there are many competing demands for resources the main decision making process centres on whether to proceed with growth and reproduction or to "hunker down" and invest in protection and survival (or to strike an optimal balance between these two processes). The transcriptional programme active at any given time largely determines which of these competing processes is dominant. At the top of the regulatory hierarchy are the sigma factors that commandeer the transcriptional machinery and determine which set of promoters are active at any given time. The regulatory inputs controlling their activity are therefore often highly complex, with multiple layers of regulation, allowing relevant environmental information to produce the most beneficial response. The tension between growth and survival is also evident in the developmental programme necessary to promote biofilm formation, which is typically associated with low growth rates and enhanced long-term survival. Nucleotide second messengers and energy pools (ATP/ADP levels) play critical roles in determining the fate of individual cells. Regulatory small RNAs frequently play important roles in the decision making processes too. In this review we discuss the trade-off that exists between reproduction and persistence in bacteria and discuss some of the recent advances in this fascinating field.

Gait risk factors for disease progression differ between non-traumatic and post-traumatic knee osteoarthritis

OBJECTIVE

To examine if relationships between knee osteoarthritis (OA) progression with knee moments and muscle activation during gait vary between patients with non-traumatic and post-traumatic knee OA.

DESIGN

This longitudinal study included participants with non-traumatic (n = 17) and post-traumatic (n = 18) knee OA; the latter group had a previous anterior cruciate ligament rupture. Motion capture cameras, force plates, and surface electromyography measured knee moments and lower extremity muscle activation during gait. Cartilage volume change were determined over 2 years using magnetic resonance imaging in four regions: medial and lateral plateau and condyle. Linear regression analysis examined relationships between cartilage change with gait metrics (moments, muscle activation), group, and their interaction.

RESULTS

Measures from knee adduction and rotation moments were related to lateral condyle cartilage loss in both groups, and knee adduction moment to lateral plateau cartilage loss in the non-traumatic group only [β = -1.336, 95% confidence intervals (CI) = -2.653 to -0.019]. Generally, lower levels of stance phase muscle activation were related to greater cartilage loss. The relationship between cartilage loss in some regions with muscle activation characteristics varied between non-traumatic and post-traumatic groups including for: lateral hamstring (lateral condyle β = 0.128, 95%CI = 0.003 to 0.253; medial plateau β = 0.199, 95%CI = 0.059 to 0.339), rectus femoris (medial condyle β = -0.267, 95%CI = -0.460 to -0.073), and medial hamstrings (medial plateau; β = -0.146, 95%CI = -0.244 to -0.048).

CONCLUSION

Findings indicate that gait risk factors for OA progression may vary between patients with non-traumatic and post-traumatic knee OA. These OA subtypes should be considered in studies that investigate gait metrics as risk factors for OA progression.

Combined Stochastic and Deterministic Processes Drive Community Assembly of Anaerobic Microbiomes During Granule Flotation

Advances in null-model approaches have resulted in a deeper understanding of community assembly mechanisms for a variety of complex microbiomes. One under-explored application is assembly of communities from the built-environment, especially during process disturbances. Anaerobic digestion for biological wastewater treatment is often underpinned by retaining millions of active granular biofilm aggregates. Flotation of granules is a major problem, resulting in process failure. Anaerobic aggregates were sampled from three identical bioreactors treating dairy wastewater. Microbiome structure was analysed using qPCR and 16S rRNA gene amplicon sequencing from DNA and cDNA. A comprehensive null-model approach quantified assembly mechanisms of floating and settled communities. Significant differences in diversity were observed between floating and settled granules, in particular, we highlight the changing abundances of Methanosaeta and Lactococcus. Both stochastic and deterministic processes were important for community assembly. Homogeneous selection was the primary mechanism for all categories, but dispersal processes also contributed. The lottery model was used to identify clade-level competition driving community assembly. Lottery “winners” were identified with different winners between floating and settled groups. Some groups changed their winner status when flotation occurred. Spirochaetaceae, for example, was only a winner in settled biomass (cDNA-level) and lost its winner status during flotation. Alternatively, Arcobacter butzerli gained winner status during flotation. This analysis provides a deeper understanding of changes that occur during process instabilities and identified groups which may be washed out—an important consideration for process control.

Simultaneous adsorption and biodegradation of trichloroethylene occurs in a biochar packed column treating contaminated landfill leachate

Trichloroethylene (TCE) is a human carcinogen that is commonly found in landfill leachate. Contaminated leachate plumes may be intercepted prior to reaching groundwater and treated in situ using permeable reactive barriers (PRB). This study used a packed column system containing herbal pomace and spruce biochar, previously shown to have TCE adsorptive capabilities. Influent containing raw or autoclaved landfill leachate was used to investigate the potential for environmental micro-organisms to establish a TCE-dechlorinating biofilm on the biochar, in order to prolong the operational life span of the system. TCE removal ≥ 99.7 % was observed by both biochars. No dichloroethylene (DCE) isomers were present in the column effluents, but cis-1,2 DCE was adsorbed to the biochar treating raw landfill leachate, indicating that dechlorination was occurring biologically in these columns. Known microbial species that are individually capable of complete dechlorination of TCE to ethene were not detected by 16S rRNA gene sequencing, but several species capable of partial TCE dechlorination (Desulfitobacterium spp., Sulfurospirillium spp. and Desulfuromonas spp) were present in the biofilms of the columns treating raw landfill leachate. These data demonstrate that biochar from waste material may be capable of supporting a dechlorinating biofilm to promote bioremediation of TCE.

Application of plasma activated water for decontamination of alfalfa and mung bean seeds

Microbial contamination of fresh produce is a major public health concern, with the number of associated disease outbreaks increasing in recent years. The consumption of sprouted beans and seeds is of particular concern, as these foodstuffs are generally consumed raw, and are produced in conditions favourable for the growth of zoonotic pathogens, if present in seeds prior to sprouting or in irrigation water. This work aimed to evaluate the activity of plasma activated water (PAW) as a disinfecting agent for alfalfa (Medicago sativa) and mung bean (Vigna radiata) seeds, during seed soaking. Each seed type was inoculated with Escherichia coli O157, E. coli O104, Listeria monocytogenes or Salmonella Montevideo, and treated with PAW for different times. A combination of PAW and ultrasound treatment was also evaluated. The germination and growth rate of both seeds were assessed after PAW treatments. PAW was demonstrated to have disinfecting ability on sprouted seeds, with reductions of up to Log₁₀ 1.67 cfu/g in alfalfa seeds inoculated with E. coli O104, and a reduction of Log₁₀ 1.76 cfu/g for mung bean seeds inoculated with E. coli O157 observed. The germination and growth rate of alfalfa and mung bean sprouts were not affected by the PAW treatments. The combination of a PAW treatment and ultrasound resulted in increased antimicrobial activity, with a reduction of Log₁₀ 3.48 cfu/g of S. Montevideo in mung bean seeds observed. These results demonstrate the potential for PAW to be used for the inactivation of pathogenic microorganisms which may be present on sprouted seeds and beans, thereby providing greater assurance of produce safety.

Landspreading with co-digested cattle slurry, with or without pasteurisation, as a mitigation strategy against pathogen, nutrient and metal contamination associated with untreated slurry

North Atlantic European grassland systems have a low nutrient use efficiency and high rainfall. This grassland is typically amended with unprocessed slurry, which counteracts soil organic matter depletion and provides essential plant micronutrients but can be mobilised during rainfall events thereby contributing to pathogen, nutrient and metal incidental losses. Co-digesting slurry with waste from food processing mitigates agriculture-associated environmental impacts but may alter microbial, nutrient and metal profiles and their transmission to watercourses, and/or soil persistence, grass yield and uptake. The impact of EU and alternative pasteurisation regimes on transmission potential of these various pollutants is not clearly understood, particularly in pasture-based agricultural systems. This study utilized simulated rainfall (Amsterdam drip-type) at a high intensity indicative of a worst-case scenario of ~11 mm hr^-1 applied to plots 1, 2, 15 and 30 days after grassland application of slurry, unpasteurised digestate, pasteurised digestate (two conditions) and untreated controls. Runoff and soil samples were collected and analysed for a suite of potential pollutants including bacteria, nutrients and metals following rainfall simulation. Grass samples were collected for three months following application to assess yield as well as nutrient and metal uptake. For each environmental parameter tested: microbial, nutrient and metal runoff losses; accumulation in soil and uptake in grass, digestate from anaerobic co-digestion of slurry with food processing waste resulted in lower pollution potential than traditional landspreading of slurry without treatment. Reduced microbial runoff from digestate was the most prominent advantage of digestate application. Pasteurisation of the digestate further augmented those environmental benefits, without impacting grass output. Anaerobic co-digestion of slurry is therefore a multi-beneficial circular approach to reducing impacts of livestock production on the environment.

A Small Study of Bacterial Contamination of Anaerobic Digestion Materials and Survival in Different Feed Stocks

If pathogens are present in feedstock materials and survive in anaerobic digestion (AD) formulations at 37 °C, they may also survive the AD process to be disseminated in digestate spread on farmland as a fertilizer. The aim of this study was to investigate the prevalence of Salmonella spp., Escherichia coli O157, Listeria monocytogenes, Enterococcus faecalis and Clostridium spp. in AD feed and output materials and survival/growth in four formulations based on food waste, bovine slurry and/or grease-trap waste using International Organization for Standardization (ISO) or equivalent methods. The latter was undertaken in 100 mL Ramboldi tubes, incubated at 37 °C for 10 d with surviving cells enumerated periodically and the T₉₀ values (time to achieve a 1 log reduction) calculated. The prevalence rates for Salmonella spp., Escherichia coli O157, Listeria monocytogenes, Enterococcus faecalis and Clostridium spp. were 3, 0, 5, 11 and 10/13 in food waste, 0, 0, 2, 3 and 2/3 in bovine slurry, 1, 0, 8, 7 and 8/8 in the mixing tank, 5, 1, 17, 18 and 17 /19 in raw digestate and 0, 0, 0, 2 and 2/2 in dried digestate, respectively. Depending on the formulation, T₉₀ values ranged from 1.5 to 2.8 d, 1.6 to 2.8 d, 3.1 to 23.5 d, 2.2 to 6.6 d and 2.4 to 9.1 d for Salmonella Newport, Escherichia coli O157, Listeria monocytogenes, Enterococcus faecalis and Clostridium sporogenes, respectively. It was concluded that AD feed materials may be contaminated with a range of bacterial pathogens and L. monocytogenes may survive for extended periods in the test formulations incubated at 37 °C.

Reactor configuration influences microbial community structure during high-rate, low-temperature anaerobic treatment of dairy wastewater

Low temperature anaerobic digestion remains in its infancy, despite increasing interest for the treatment of complex wastewaters. In this study, the feasibility of low-temperature anaerobic treatment of dairy wastewater was assessed during a 443-day laboratory-scale bioreactor trial. The bioreactors were operated in triplicate at organic loading rates of 7.5-9 kgCODm^-3d^-1 throughout five operational phases. The structure of the microbial community was analysed using quantitative real-time PCR and amplicon sequencing of 16S rRNA genes from DNA and rRNA. The results indicated that low-temperature treatment of dairy wastewater is feasible at 15 °C, but that reactor configuration remains extremely important. The upflow anaerobic sludge bed (UASB) configuration out-performed the expanded granular sludge bed (EGSB)-based configurations. Decreased temperatures resulted in significant reductions in microbiome diversity. Methanosaeta was identified as a dominant genus throughout the trial, while Lactococcus was identified as an important bacterial genus at low-temperatures. However, the relative abundance of Lactococcus was significantly influenced by reactor configuration.

Easy phylotyping of Escherichia coli via the EzClermont web app and command-line tool

The Clermont PCR method for phylotyping Escherichia coli remains a useful classification scheme even though genome sequencing is now routine, and higher-resolution sequence typing schemes are now available. Relating present-day whole-genome E. coli classifications to legacy phylotyping is essential for harmonizing the historical literature and understanding of this important organism. Therefore, we present EzClermont – a novel in silico Clermont PCR phylotyping tool to enable ready application of this phylotyping scheme to whole-genome assemblies. We evaluate this tool against phylogenomic classifications, and an alternative software implementation of Clermont typing. EzClermont is available as a web app at www.ezclermont.org, and as a command-line tool at https://nickp60.github.io/EzClermont/.

FRI0417 IDENTIFICATION OF THE MOST IMPORTANT FEATURES OF KNEE OSTEOARTHRITIS PROGRESSORS USING MACHINE LEARNING METHODS

Background:

Knee osteoarthritis (OA), a leading cause of disability worldwide, can be difficult to define as its development is often insidious and involves different subgroups. We still lack robust prediction models that are able to guide clinical decisions and stratify OA patients according to risk of disease progression.

Objectives:

This study aimed at identifying the most important features of knee OA progressors. To this end, we used machine learning (ML) algorithms on a large set of subjects and features to develop advanced prediction models that provide high classification and prediction performance.

Methods:

Participants, features and outcomes were from the Osteoarthritis Initiative. Features were from baseline (1107), including articular knee tissues (135) assessed by quantitative MRI. OA progressors were ascertained by four outcomes: cartilage volume loss in medial plateau at 48 and 96 months (Prop_CV_48M, 96M); Kellgren-Lawrence (KL) grade ≥2; and medial joint space narrowing (JSN) ≥1 at 48 months. Subjects’ numbers were as follows: 1598 for the outcome Prop_CV_96M, 1044 for the Prop_CV_48M, and 1468 for each KL grade ≥2 at 48 months and JSN ≥1 at 48 months. Six feature selection models were used to identify the common features in each outcome. Six classification methods were applied to measure the accuracy of the selected features in classifying the subjects into progressors and non-progressors. Classification of the best features was done using auto-ML interface and the area under the curve (AUC). To prioritize the top features, Sparse Partial Least Square (sPLS) method was used.

Results:

For the classification of the best common features in each outcome, Multi-Layer Perceptron (MLP) achieved the highest AUC in Prop_CV_96M, KL, and JSN (0.80, 0.88, 0.95), and Gradient Boosting Machine (GBM) for Prop_CV_48M (0.70). sPLS revealed that the baseline top five features to predict knee OA progressors are the joint space width (JSW), mean cartilage thickness of peripheral, medial, and central tibial plateau, and JSN.

Conclusion:

This is the first time that such a comprehensive study was performed for identifying the best features and classification methods for knee OA progressors. Data revealed that early prediction of knee OA progression can be done with high accuracy and based on only a few features. This study identifies the baseline X-ray and MRI-based features as the most important for predicting knee OA progressors. These results could be used for the development of a tool enabling prediction of knee OA progressors.

Acknowledgments:

This work was supported in part by the Osteoarthritis Research Unit of the University of Montreal Hospital Research Centre; the Chair in Osteoarthritis, University of Montreal, (both from Montreal, Quebec, Canada); and the Computational Biology Laboratory, Laval University Hospital Research Center, (Québec, Quebec, Canada). A Jamshidi received a bursary from the Canada First Research Excellence Fund through TransMedTech Institute, (Montreal, Quebec, Canada).

Disclosure of Interests:

Afshin Jamshidi: None declared, Mickaël Leclercq: None declared, Aurelie Labbe: None declared, Jean-Pierre Pelletier Shareholder of: ArthroLab Inc., Grant/research support from: TRB Chemedica, Speakers bureau: TRB Chemedica and Mylan, François Abram Employee of: ArthroLab Inc., Arnaud Droit: None declared, Johanne Martel-Pelletier Shareholder of: ArthroLab Inc., Grant/research support from: TRB Chemedica

FRI0416 COMBINATION OF SERUM ADIPOKINES/RELATED INFLAMMATORY FACTORS AND RATIOS AS PREDICTORS OF INFRAPATELLAR FAT PAD VOLUME IN KNEE OSTEOARTHRITIS PATIENTS: USAGE OF A COMPREHENSIVE MACHINE LEARNING APPROACH

Background:

One of the hurdles in osteoarthritis (OA) drug discovery and the improvement of therapeutic approaches is the early identification of patients who will progress. It is therefore crucial to find efficient and reliable means of screening OA progressors. Although the main risk factors, age, gender and body mass index (BMI), are important, they alone are poor predictors. However, serum factors could be potential biomarkers for early prediction of knee OA progression.

Objectives:

In a first step toward finding early reliable predictors of OA progressors, this study aimed to determine, in OA individuals, the optimum combination of serum levels of adipokines/related inflammatory factors, their ratios, and the three main OA risk factors for predicting knee OA infrapatellar fat pad (IPFP) volume, as this tissue has been associated with knee OA onset and progression.

Methods:

Serum and magnetic resonance images (MRI) were from the Osteoarthritis Initiative at baseline. Variables (48) comprised the 3 main OA risk factors (age, gender, BMI), 6 adipokines, 3 inflammatory factors, and their 36 ratios. IPFP volume was assessed on MRI with a neural network methodology. The best variables and models were identified in Total cohort (n=678), High-BMI (n=341) and Low-BMI (n=337), using an artificial intelligence selection approach: the adaptive neuro-fuzzy inference system embedded with fuzzy c-means clustering (ANFIS-FCM). Performance was validated using uncertainty analyses and statistical indices. Reproducibility was done using 80 OA patients from a clinical trial (female, n=57; male, n=23).

Results:

For the three groups, 8.44E+14 sub-variables were investigated and 48 models were selected. The best model for each group included five variables: the three risk factors and adipsin/C-reactive protein combined for Total cohort, adipsin/chemerin; High-BMI, chemerin/adiponectin high molecular weight; and Low-BMI, interleukin-8. Data also revealed that the main form of the ratio used for the model was justified, as the use of the inverse form slightly decreased the performance of the model in both training and testing stages. Further investigation indicated that gender improved (13-16%) the prediction results compared to the BMI-based models. For each gender, we then generated a pseudocode (an evolutionary computation equation) with the 5 variables for predicting IPFP volume. Reproducibility experiments were excellent (correlation coefficient: female 0.83, male 0.95).

Conclusion:

This study demonstrates, for the first time, that the combination of the serum levels of adipokines/inflammatory factors and the three main risk factors of OA could predict IPFP volume with high reproducibility, and superior performance with gender separation. By using the models for each gender and the pseudocodes for OA patients provided in this study, the next step will be to develop a predictive model for OA progressors.

Acknowledgments:

This work was funded by the Chair in Osteoarthritis of the University of Montreal, the Osteoarthritis Research Unit of the University of Montreal Hospital Research Centre, the Groupe de recherches des maladies rhumatismales du Québec and by ArthroLab Inc., all from Montreal, Quebec, Canada.

Disclosure of Interests:

Hossein Bonakdari: None declared, Ginette Tardif: None declared, François Abram Employee of: ArthroLab Inc., Jean-Pierre Pelletier Shareholder of: ArthroLab Inc., Grant/research support from: TRB Chemedica, Speakers bureau: TRB Chemedica and Mylan, Johanne Martel-Pelletier Shareholder of: ArthroLab Inc., Grant/research support from: TRB Chemedica

OP0303 CORTICOSTEROID INJECTION IN KNEE OSTEOARTHRITIS IS ASSOCIATED WITH REDUCTION IN MENISCAL THICKNESS AND JOINT SPACE WIDTH WITH NO EFFECT ON CARTILAGE THICKNESS: A CASE CONTROL STUDY

Background:

Intra-articular corticosteroid injections (IACI) are commonly used for the treatment of symptomatic knee osteoarthritis (OA) and therapeutic guidelines have recommended their use. However, their safety regarding the evolution of structural changes remains unknown.

Objectives:

This study explored the effects of IACI on the evolution of knee OA structural changes assessed by magnetic resonance imaging (MRI).

Methods:

Participants were selected from the Osteoarthritis Initiative database. In this nested case-control design study, participants who received one treatment with IACI and had MRI exams available at the yearly follow-up visits before (pre-treatment), during (treatment), and after (post-treatment) were defined as “cases”. Each case was matched with one control for age, gender, body mass index (BMI), height, joint space width (JSW), cartilage volume, bone marrow lesion (BML), meniscal extrusion, and Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) pain at baseline. Ninety-three (93) participants fulfilling the inclusion criteria were selected and matched to controls (n=93). The study structural variables were MRI (cartilage volume, meniscal thickness, bone marrow lesion (BML), bone curvature), X-rays (JSW), and symptoms (WOMAC pain), assessed at the yearly consecutive visits and changes measured within the follow-up periods.

Results:

At baseline, the control and treatment groups were balanced. In the pre-treatment period, the cartilage volume loss in the medial compartment was significantly greater in the IACI (p=0.006) compared to the control group, with a numerical trend (p=0.071) in the lateral compartment. In the treatment period, the cartilage loss was not different between groups, with the exception of a significantly greater loss in the lateral compartment in the IACI group (p=0.041). In the post-treatment period there was no difference in the cartilage loss between the groups in both compartments. For the meniscal thickness loss in the pre-treatment period, no difference was found between groups; however, there was a significantly greater loss (p=0.007) during the treatment period in the IACI. In the post-treatment period, the loss of the medial meniscus was similar in both groups. For the lateral meniscus, there was no significant difference at any time between the two groups. The loss in JSW in the pre- and post-treatment periods was not different between groups, but was significantly greater (p=0.011) in the IACI group in the treatment period. The changes in the BML sizes over time were small and similar between groups. For the bone curvature, IACI group showed a smaller change compared to the control (p=0.037) at the treatment period. The WOMAC pain changes in both groups were small and unlikely to be clinically relevant.

Conclusion:

This study provides evidence that in knee OA, IACI were not associated with the occurrence of any deleterious effect on knee structures post-treatment, including cartilage volume and loss. The increase in the rate loss of medial meniscal thickness, which was associated with a loss of JSW, was a transient phenomenon and its clinical relevance unknown at that time.

Acknowledgments:

This initiative was funded by a grant from La Chaire en arthrose de l’Université de Montréal, and by ArthroLab Inc. (both in Montreal, Quebec, Canada).

Disclosure of Interests:

Jean-Pierre Pelletier Shareholder of: ArthroLab Inc., Grant/research support from: TRB Chemedica, Speakers bureau: TRB Chemedica and Mylan, Jean-Pierre Raynauld Consultant of: ArthroLab Inc., François Abram Employee of: ArthroLab Inc., Marc Dorais Consultant of: ArthroLab Inc., Patrice Paiement Employee of: ArthroLab Inc., Johanne Martel-Pelletier Shareholder of: ArthroLab Inc., Grant/research support from: TRB Chemedica

Pyrolysed waste materials show potential for remediation of trichloroethylene-contaminated water

Trichloroethylene (TCE) is an Environmental Protection Agency priority pollutant associated with cancer in humans. With numerous industrial applications and regular landfill disposal, TCE is a common landfill leachate pollutant. In situ treatment barriers use costly fill materials such as granular activated carbon (GAC). Here, we show that while a range of untreated waste materials had little ability to adsorb TCE, waste-derived biochar showed excellent capacity for TCE adsorption. TCE removal efficiencies by spruce and oak-derived biochars were > 99.5 %, outperforming GAC (95 %) and herbal pomace biochar (93 %). A contact time of at least 32 h was required to reach equilibrium for all of these media. Assessment of pollution swapping potential revealed release of phosphate by all biochars. Analysis of media surface characteristics by Fourier Transform Infrared Spectroscopy (FTIR) predicted that GAC should have the highest ability to adsorb TCE, followed by Oak Biochar, Herbal Pomace Biochar 1, and Spruce Biochar 2, which was not in agreement with the experimental adsorption data. These data demonstrate the potential for pyrolysed waste material to be used as an alternative fill material for in situ remediation applications, thereby also addressing the European Circular Economy Strategy.

Chordomics: a visualization tool for linking function to phylogeny in microbiomes

SUMMARY

The overarching aim of microbiome analysis is to uncover the links between microbial phylogeny and function in order to access ecosystem functioning. This can be done using several experimental strategies targeting different biomolecules, including DNA (metagenomics), RNA (metatranscriptomics) and proteins (metaproteomics). Despite the importance of linking microbial function to phylogeny there are currently no visualization tools that effectively integrate this information. Chordomics is a Shiny-based application for linked -omics data analysis, allowing users to visualize microbial function and phylogeny on a single plot and compare datasets across time and environments.

AVAILABILITY AND IMPLEMENTATION

Chordomics is available on GitHub: https://github.com/kevinmcdonnell6/chordomics; software is coded in R and JavaScript and a demonstration version is available at https://kmcd.shinyapps.io/ChordomicsDemo/.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Impact of beef extract used for sample concentration on the detection of Escherichia coli DNA in water samples via qPCR

There is increasing interest in methodologies for the simultaneous concentration and detection of multiple targets in individual samples. The aim of this study was to investigate the potential presence of E. coli DNA in beef extract powder used as part of a procedure to concentrate water samples for the simultaneous detection of bacteria, viruses and protozoa. DNA from E. coli was detected in five out of six beef extract lots tested, demonstrating the limitations of its inclusion when being used in assays that will be used for the detection of E. coli in water samples. Further work is required to clarify if this phenomenon also occurs for other microorganisms of interest in water.

The potential for polyphosphate metabolism in Archaea and anaerobic polyphosphate formation in Methanosarcina mazei

Inorganic polyphosphate (polyP) is ubiquitous across all forms of life, but the study of its metabolism has been mainly confined to bacteria and yeasts. Few reports detail the presence and accumulation of polyP in Archaea, and little information is available on its functions and regulation. Here, we report that homologs of bacterial polyP metabolism proteins are present across the major taxa in the Archaea, suggesting that archaeal populations may have a greater contribution to global phosphorus cycling than has previously been recognised. We also demonstrate that polyP accumulation can be induced under strictly anaerobic conditions, in response to changes in phosphate (Pi) availability, i.e. Pi starvation, followed by incubation in Pi replete media (overplus), in cells of the methanogenic archaeon Methanosarcina mazei. Pi-starved M. mazei cells increased transcript abundance of the alkaline phosphatase (phoA) gene and of the high-affinity phosphate transport (pstSCAB-phoU) operon: no increase in polyphosphate kinase 1 (ppk1) transcript abundance was observed. Subsequent incubation of Pi-starved M. mazei cells under Pi replete conditions, led to a 237% increase in intracellular polyphosphate content and a > 5.7-fold increase in ppk1 gene transcripts. Ppk1 expression in M. mazei thus appears not to be under classical phosphate starvation control.

Microbial Contamination of Fresh Produce: What, Where, and How?

Promotion of healthier lifestyles has led to an increase in consumption of fresh produce. Such foodstuffs may expose consumers to increased risk of foodborne disease, as often they are not subjected to processing steps to ensure effective removal or inactivation of pathogenic microorganisms before consumption. Consequently, reports of ready-to-eat fruit and vegetable related disease outbreak occurrences have increased substantially in recent years, and information regarding these events is often not readily available. Identifying the nature and source of microbial contamination of these foodstuffs is critical for developing appropriate mitigation measures to be implemented by food producers. This review aimed to identify the foodstuffs most susceptible to microbial contamination and the microorganisms responsible for disease outbreaks from information available in peer-reviewed scientific publications. A total of 571 outbreaks were identified from 1980 to 2016, accounting for 72,855 infections and 173 deaths. Contaminated leafy green vegetables were responsible for 51.7% of reported outbreaks. Contaminated soft fruits caused 27.8% of infections. Pathogenic strains of Escherichia coli and Salmonella, norovirus, and hepatitis A accounted for the majority of cases. Large outbreaks resulted in particular biases such as the observation that contaminated sprouted plants caused 31.8% of deaths. Where known, contamination mainly occurred via contaminated seeds, water, and contaminated food handlers. There is a critical need for standardized datasets regarding all aspects of disease outbreaks, including how foodstuffs are contaminated with pathogenic microorganisms. Providing food business operators with this knowledge will allow them to implement better strategies to improve safety and quality of fresh produce.

The ratio adipsin/MCP-1 is strongly associated with structural changes and CRP/MCP-1 with symptoms in obese knee osteoarthritis subjects: data from the Osteoarthritis Initiative

OBJECTIVE

There is a need to identify reliable biomarkers that can predict knee osteoarthritis (OA) progression. We investigated a panel of adipokines and some related inflammatory factors alone and their ratios for their associative value at assessing cartilage volume loss over time and symptoms in obese [High body mass index (BMI)] and non-obese (Low BMI) OA subjects.

DESIGN

Human OA serum was from the Osteoarthritis Initiative Progression subcohort. Baseline levels of adiponectin (high and low molecular weight forms), adipsin, chemerin, leptin, visfatin, C-reactive protein (CRP), interleukin-8 (IL-8) and monocyte chemoattractant protein-1 (MCP-1) were evaluated with specific assays. Cartilage volume was assessed at baseline and 48 months by quantitative magnetic resonance imaging (MRI), and symptoms using baseline Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) scores. Data were analysed by linear regression with confounding factors at baseline, followed by multiple comparison adjustment.

RESULTS

The levels of the nine biomarkers and their ratios (36) were studied. Among High BMI subjects, only the ratio adipsin/MCP-1 was associated with cartilage volume loss over time in the lateral compartment [β, -2.95; 95% confidence interval (CI), -4.42, -1.49; P = 0.010], whereas MCP-1 was associated with WOMAC pain (-1.74; -2.75, -0.73; P = 0.030) and the ratio CRP/MCP-1 with WOMAC pain (0.76; 0.37, 1.14; P = 0.023), function (2.43; 1.20, 3.67; P = 0.020) and total (3.29; 1.58, 5.00; P = 0.027). No associations were found for biomarkers or ratios in Low BMI OA.

CONCLUSION

In this study, the ratio adipsin/MCP-1 was found to be associated with the knee structural changes and that of CRP/MCP-1 with symptoms in obese OA subjects. Our data further underline the relevance of ratios as biomarkers to a stronger association to OA progression and symptoms.

riboSeed: leveraging prokaryotic genomic architecture to assemble across ribosomal regions

The vast majority of bacterial genome sequencing has been performed using Illumina short reads. Because of the inherent difficulty of resolving repeated regions with short reads alone, only ∼10% of sequencing projects have resulted in a closed genome. The most common repeated regions are those coding for ribosomal operons (rDNAs), which occur in a bacterial genome between 1 and 15 times, and are typically used as sequence markers to classify and identify bacteria. Here, we exploit the genomic context in which rDNAs occur across taxa to improve assembly of these regions relative to de novo sequencing by using the conserved nature of rDNAs across taxa and the uniqueness of their flanking regions within a genome. We describe a method to construct targeted pseudocontigs generated by iteratively assembling reads that map to a reference genome’s rDNAs. These pseudocontigs are then used to more accurately assemble the newly sequenced chromosome. We show that this method, implemented as riboSeed, correctly bridges across adjacent contigs in bacterial genome assembly and, when used in conjunction with other genome polishing tools, can assist in closure of a genome.

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

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

Relationship between alignment and cartilage thickness in patients with non-traumatic and post-traumatic knee osteoarthritis

OBJECTIVE

To compare cartilage thickness between patients with non-traumatic and post-traumatic knee osteoarthritis (OA) and healthy controls and to determine if disease severity and alignment impact these differences.

DESIGN

Participants with non-traumatic (n = 22) and post-traumatic (n = 19) knee OA, and healthy controls (n = 22) were recruited for this cross-sectional study. Participants underwent 3T magnetic resonance imaging (T1-weighted, 3D sagittal gradient echo sequence) and cartilage thickness was determined in four regions: medial and lateral condyle, and medial and lateral plateau. Lower extremity alignment (mechanical axis angle) and disease severity (Kellgren-Lawrence scores) were measured from full length radiographs. Statistical analysis included one-way analysis of variance (ANOVA) and modified Bonferroni test adjusting for multiple pairwise comparisons. Linear regression analyses examined the relationship between cartilage thickness and knee OA group after controlling for disease severity, meniscal status, and alignment.

RESULTS

In participants with predominantly medial compartment knee OA, compared to healthy controls, those with non-traumatic knee OA had diminished cartilage thickness in the medial plateau (p = 0.035) and those with post-traumatic knee OA had greater cartilage thickness in the lateral condyle (p = 0.044). In the lateral condyle, data revealed that alignment accounted for the variance in cartilage thickness (p = 0.035), in which a stronger relationship was found in the non-traumatic (r = -0.61) than the post-traumatic (r = -0.12) OA group.

CONCLUSIONS

Emerging data demonstrated that participants with non-traumatic knee OA have a stronger relationship between alignment and cartilage thickness than those with post-traumatic knee OA. This indicates that factors involved in knee OA initiation and progression may differ between these OA subtypes.

Absence of Curli in Soil-Persistent Escherichia coli Is Mediated by a C-di-GMP Signaling Defect and Suggests Evidence of Biofilm-Independent Niche Specialization

Escherichia coli is commonly viewed as a gastrointestinal commensal or pathogen although an increasing body of evidence suggests that it can persist in non-host environments as well. Curli are a major component of biofilm in many enteric bacteria including E. coli and are important for adherence to different biotic and abiotic surfaces. In this study we investigated curli production in a unique collection of soil-persistent E. coli isolates and examined the role of curli formation in environmental persistence. Although most soil-persistent E. coli were curli-positive, 10% of isolates were curli-negative (17 out of 170). Curli-producing E. coli (COB583, COB585, and BW25113) displayed significantly more attachment to quartz sand than the curli-negative strains. Long-term soil survival experiments indicated that curli production was not required for long-term survival in live soil (over 110 days), as a curli-negative mutant BW25113ΔcsgB had similar survival compared to wild type BW25113. Mutations in two genes associated with c-di-GMP metabolism, dgcE and pdeR, correlated with loss of curli in eight soil-persistent strains, although this did not significantly impair their survival in soil compared to curli-positive strains. Overall, the data indicate that curli-deficient and biofilm-defective strains, that also have a defect in attachment to quartz sand, are able to reside in soil for long periods of time thus pointing to the possibility that niches may exist in the soil that can support long-term survival independently of biofilm formation.

Reproducible, high-yielding, biological caproate production from food waste using a single-phase anaerobic reactor system

BACKGROUND

Nowadays, the vast majority of chemicals are either synthesised from fossil fuels or are extracted from agricultural commodities. However, these production approaches are not environmentally and economically sustainable, as they result in the emission of greenhouse gases and they may also compete with food production. Because of the global agreement to reduce greenhouse gas emissions, there is an urgent interest in developing alternative sustainable sources of chemicals. In recent years, organic waste streams have been investigated as attractive and sustainable feedstock alternatives. In particular, attention has recently focused on the production of caproate from mixed culture fermentation of low-grade organic residues. The current approaches for caproate synthesis from organic waste are not economically attractive, as they involve the use of two-stage anaerobic digestion systems and the supplementation of external electron donors, both of which increase its production costs. This study investigates the feasibility of producing caproate from food waste (FW) without the supplementation of external electron donors using a single-phase reactor system.

RESULTS

Replicate leach-bed reactors were operated on a semi-continuous mode at organic loading of 80 g VS FW l-1 and at solid retention times of 14 and 7 days. Fermentation, rather than hydrolysis, was the limiting step for caproate production. A higher caproate production yield 21.86 ± 0.57 g COD l-1 was achieved by diluting the inoculating leachate at the beginning of each run and by applying a leachate recirculation regime. The mixed culture batch fermentation of the FW leachate was able to generate 23 g caproate COD l-1 (10 g caproate l-1), at a maximum rate of 3 g caproate l-1 day-1 under high H2 pressure. Lactate served as the electron donor and carbon source for the synthesis of caproate. Microbial community analysis suggested that neither Clostridium kluyveri nor Megasphaera elsdenii, which are well-characterised caproate producers in bioreactors systems, were strongly implicated in the synthesis of caproate, but that rather Clostridium sp. with 99% similarity to Ruminococcaceae bacterium CPB6 and Clostridium sp. MT1 likely played key roles in the synthesis of caproate. This finding indicates that the microbial community capable of caproate synthesis could be diverse and may therefore help in maintaining a stable and robust process.

CONCLUSIONS

These results indicate that future, full-scale, high-rate caproate production from carbohydrate-rich wastes, associated with biogas recovery, could be envisaged.

Linking Microbial Community Structure and Function During the Acidified Anaerobic Digestion of Grass

Harvesting valuable bioproducts from various renewable feedstocks is necessary for the critical development of a sustainable bioeconomy. Anaerobic digestion is a well-established technology for the conversion of wastewater and solid feedstocks to energy with the additional potential for production of process intermediates of high market values (e.g., carboxylates). In recent years, first-generation biofuels typically derived from food crops have been widely utilized as a renewable source of energy. The environmental and socioeconomic limitations of such strategy, however, have led to the development of second-generation biofuels utilizing, amongst other feedstocks, lignocellulosic biomass. In this context, the anaerobic digestion of perennial grass holds great promise for the conversion of sustainable renewable feedstock to energy and other process intermediates. The advancement of this technology however, and its implementation for industrial applications, relies on a greater understanding of the microbiome underpinning the process. To this end, microbial communities recovered from replicated anaerobic bioreactors digesting grass were analyzed. The bioreactors leachates were not buffered and acidic pH (between 5.5 and 6.3) prevailed at the time of sampling as a result of microbial activities. Community composition and transcriptionally active taxa were examined using 16S rRNA sequencing and microbial functions were investigated using metaproteomics. Bioreactor fraction, i.e., grass or leachate, was found to be the main discriminator of community analysis across the three molecular level of investigation (DNA, RNA, and proteins). Six taxa, namely Bacteroidia, Betaproteobacteria, Clostridia, Gammaproteobacteria, Methanomicrobia, and Negativicutes accounted for the large majority of the three datasets. The initial stages of grass hydrolysis were carried out by Bacteroidia, Gammaproteobacteria, and Negativicutes in the grass biofilms, in addition to Clostridia in the bioreactor leachates. Numerous glycolytic enzymes and carbohydrate transporters were detected throughout the bioreactors in addition to proteins involved in butanol and lactate production. Finally, evidence of the prevalence of stressful conditions within the bioreactors and particularly impacting Clostridia was observed in the metaproteomes. Taken together, this study highlights the functional importance of Clostridia during the anaerobic digestion of grass and thus research avenues allowing members of this taxon to thrive should be explored.

Stabilisation of spent mushroom substrate for application as a plant growth-promoting organic amendment

Over three million tonnes of spent mushroom substrate (SMS) are produced in Europe every year as a by-product of the cultivation of Agaricus bisporus. The management of SMS has become an increasing challenge for the mushroom production industry, and finding environmentally and economically sustainable solutions for this organic residue is, therefore, highly desirable. Due to its physical properties and nutrient content, SMS has great potential to be employed in agricultural and horticultural sectors, and further contribute to reduce the use of non-renewable resources, such as peat. However, SMS is often regarded as not being stable and/or mature, which hampers its wide use for crop production. Here, we demonstrate the stabilisation of SMS and its subsequent use as organic fertiliser and partial peat replacement in horticulture. The stabilisation was performed in a laboratory-scale composting system, with controlled temperature and aeration. Physical and chemical parameters were monitored during composting and provided information on the progress of the process. Water soluble carbohydrates (WSC) content was found to be the most reliable parameter to predict SMS stability. In situ oxygen consumption indicated the main composting phases, reflecting major changes in microbial activity. The structure of the bacterial community was also found to be a potential predictor of stability, as the compositional changes followed the composting progress. By contrast, the fungal community did not present clear successional process along the experiment. Maturity and quality of the stabilised SMS were assessed in a horticultural growing trial. When used as the sole fertiliser source, SMS was able to support Lolium multiflorum (Italian ryegrass) growth and significantly improved grass yield with a concentration-dependent response, increasing grass biomass up to 300%, when compared to the untreated control. In summary, the results indicated that the method employed was efficient in generating a stable and mature product, which has a great potential to be applied in horticulture. This study represents a step forward in the management of SMS residue, and also provides an alternative to reduce the use of peat in horticulture, alleviating environmental impacts to peatland ecosystems.

Agricultural anaerobic digestion power plants in Ireland and Germany: policy and practice

The process of anaerobic digestion (AD) is valued as a carbon-neutral energy source, while simultaneously treating organic waste, making it safer for disposal or use as a fertilizer on agricultural land. The AD process in many European nations, such as Germany, has grown from use of small, localized digesters to the operation of large-scale treatment facilities, which contribute significantly to national renewable energy quotas. However, these large AD plants are costly to run and demand intensive farming of energy crops for feedstock. Current policy in Germany has transitioned to support funding for smaller digesters, while also limiting the use of energy crops. AD within Ireland, as a new technology, is affected by ambiguous governmental policies concerning waste and energy. A clear governmental strategy supporting on-site AD processing of agricultural waste will significantly reduce Ireland's carbon footprint, improve the safety and bioavailability of agricultural waste, and provide an indigenous renewable energy source. © 2016 Society of Chemical Industry.

Functional responses and adaptation of mesophilic microbial communities to psychrophilic anaerobic digestion

Psychrophilic (<20°C) anaerobic digestion (AD) represents an attractive alternative to mesophilic wastewater treatment. In order to investigate the AD microbiome response to temperature change, with particular emphasis on methanogenic archaea, duplicate laboratory-scale AD bioreactors were operated at 37°C followed by a temperature drop to 15°C. A volatile fatty acid-based wastewater (composed of propionic acid, butyric acid, acetic acid and ethanol) was used to provide substrates representing the later stages of AD. Community structure was monitored using 16S rRNA gene clone libraries, as well as DNA and cDNA-based DGGE analysis, while the abundance of relevant methanogens was followed using qPCR. In addition, metaproteomics, microautoradiography-fluorescence in situ hybridization, and methanogenic activity measurements were employed to investigate microbial activities and functions. Methanomicrobiales abundance increased at low temperature, which correlated with an increased contribution of CH4 production from hydrogenotrophic methanogenesis at 15°C. Methanosarcinales utilized acetate and H2/CO2 as CH4 precursors at both temperatures and a partial shift from acetoclastic to hydrogenotrophic methanogenesis was observed for this archaeal population at 15°C. An upregulation of protein expression was reported at low temperature as well as the detection of chaperones indicating that mesophilic communities experienced stress during long-term exposure to 15°C. Overall, changes in microbial community structure and function were found to underpin the adaptation of mesophilic sludge to psychrophilic AD.

Low-temperature anaerobic digestion is associated with differential methanogenic protein expression

Anaerobic digestion (AD) is an attractive wastewater treatment technology, leading to the generation of recoverable biofuel (methane). Most industrial AD applications, carry excessive heating costs, however, as AD reactors are commonly operated at mesophilic temperatures while handling waste streams discharged at ambient or cold temperatures. Consequently, low-temperature AD represents a cost-effective strategy for wastewater treatment. The comparative investigation of key microbial groups underpinning laboratory-scale AD bioreactors operated at 37, 15 and 7°C was carried out. Community structure was monitored using 16S rRNA clone libraries, while abundance of the most prominent methanogens was investigated using qPCR. In addition, metaproteomics was employed to access the microbial functions carried out in situ. While δ-Proteobacteria were prevalent at 37°C, their abundance decreased dramatically at lower temperatures with inverse trends observed for Bacteroidetes and Firmicutes. Methanobacteriales and Methanosaeta were predominant at all temperatures investigated while Methanomicrobiales abundance increased at 15°C compared to 37 and 7°C. Changes in operating temperature resulted in the differential expression of proteins involved in methanogenesis, which was found to occur in all bioreactors, as corroborated by bioreactors' performance. This study demonstrated the value of employing a polyphasic approach to address microbial community dynamics and highlighted the functional redundancy of AD microbiomes.

Systems-based approaches to unravel multi-species microbial community functioning

Some of the most transformative discoveries promising to enable the resolution of this century's grand societal challenges will most likely arise from environmental science and particularly environmental microbiology and biotechnology. Understanding how microbes interact in situ, and how microbial communities respond to environmental changes remains an enormous challenge for science. Systems biology offers a powerful experimental strategy to tackle the exciting task of deciphering microbial interactions. In this framework, entire microbial communities are considered as metaorganisms and each level of biological information (DNA, RNA, proteins and metabolites) is investigated along with in situ environmental characteristics. In this way, systems biology can help unravel the interactions between the different parts of an ecosystem ultimately responsible for its emergent properties. Indeed each level of biological information provides a different level of characterisation of the microbial communities. Metagenomics, metatranscriptomics, metaproteomics, metabolomics and SIP-omics can be employed to investigate collectively microbial community structure, potential, function, activity and interactions. Omics approaches are enabled by high-throughput 21st century technologies and this review will discuss how their implementation has revolutionised our understanding of microbial communities.

Adhesive proteins of stalked and acorn barnacles display homology with low sequence similarities

Barnacle adhesion underwater is an important phenomenon to understand for the prevention of biofouling and potential biotechnological innovations, yet so far, identifying what makes barnacle glue proteins ‘sticky’ has proved elusive. Examination of a broad range of species within the barnacles may be instructive to identify conserved adhesive domains. We add to extensive information from the acorn barnacles (order Sessilia) by providing the first protein analysis of a stalked barnacle adhesive, Lepas anatifera (order Lepadiformes). It was possible to separate the L. anatifera adhesive into at least 10 protein bands using SDS-PAGE. Intense bands were present at approximately 30, 70, 90 and 110 kilodaltons (kDa). Mass spectrometry for protein identification was followed by de novo sequencing which detected 52 peptides of 7–16 amino acids in length. None of the peptides matched published or unpublished transcriptome sequences, but some amino acid sequence similarity was apparent between L. anatifera and closely-related Dosima fascicularis. Antibodies against two acorn barnacle proteins (ab-cp-52k and ab-cp-68k) showed cross-reactivity in the adhesive glands of L. anatifera. We also analysed the similarity of adhesive proteins across several barnacle taxa, including Pollicipes pollicipes (a stalked barnacle in the order Scalpelliformes). Sequence alignment of published expressed sequence tags clearly indicated that P. pollicipes possesses homologues for the 19 kDa and 100 kDa proteins in acorn barnacles. Homology aside, sequence similarity in amino acid and gene sequences tended to decline as taxonomic distance increased, with minimum similarities of 18–26%, depending on the gene. The results indicate that some adhesive proteins (e.g. 100 kDa) are more conserved within barnacles than others (20 kDa).