Jennifer Mattock’s research while affiliated with Scotland's Rural College and other places

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Publications (19)


Schematic representation of the experimental timeline. Data was recorded during the 56-day performance testing period and methane emissions during the 3-day-long respiration chamber period. T1 to T6 represent each of the timepoints in which the rumen digesta was sampled from live animals. T6 corresponds to shortly after slaughter.
Rumen microbial genera. Stacked bar chart of the ten microbial genera with the highest average relative abundances over all timepoints and animals. Rpt refers to repeatability, analysed across both diets. Microbial genera without an Rpt value were not significantly repeatable in this analysis.
Clustering of samples based on beta diversity. Non-metric multi-dimensional scaling (NMDS) plot of Bray–Curtis distances between samples at a microbial genera and b microbial genes level. The stress values of < 0.2 above the panels indicate that the two-dimensional plot is a fair representation of the original high-dimensional distances with some acceptable distortion.
Correlations between microbiome profiles of different timepoints. Pearson correlations between vectorized matrices of (a) 515 microbial genera (MT) and 417 microbial genes (MG), (b) 412 MT and 376 MG from animals fed concentrate (CON), and (c) 223 MT and 165 MG from animals fed forage (FOR), respectively. MT and MG abundances were centred and additive log-ratio transformed and then centred based on their mean abundance throughout all timepoints. Correlations of MT profiles from different timepoints are represented above the diagonal and MG are represented below the diagonal.
Proportion of variance of each trait explained by repeatable microbiome features in six timepoints. Phenotypes (feed conversion ratio, average daily gain, daily feed intake, residual feed intake, methane yield and daily methane production) were predicted using partial least squares models including as explanatory variables different sets of microbial genera (all (i.e., 1050), 515 repeatable across both diets, 412 repeatable within concentrate-fed animals, 223 repeatable within forage-fed animals, and stableMT) or microbial genes (all (i.e., 1901), 417 repeatable across both diets, 376 repeatable within concentrate-fed animals, 165 repeatable within forage-fed animals, and stableMG). Each pie chart is read counterclockwise, in a cumulative manner; for example, using 1050 microbial genera from timepoints T3, T6, T5, T4, T1, and T2 explains 64.4%, 67.9%, 71.4%, 73.1%, 76.2% and 77.2%, respectively, of the variance in feed conversion ratio.

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Temporal stability of the rumen microbiome and its longitudinal associations with performance traits in beef cattle
  • Article
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September 2024

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117 Reads

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Marina Martínez-Álvaro

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Jennifer Mattock

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[...]

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The rumen microbiome is the focus of a growing body of research, mostly based on investigation of rumen fluid samples collected once from each animal. Exploring the temporal stability of rumen microbiome profiles is imperative, as it enables evaluating the reliability of findings obtained through single-timepoint sampling. We explored the temporal stability of rumen microbiomes considering taxonomic and functional aspects across the 7-month growing-finishing phase spanning 6 timepoints. We identified a temporally stable core microbiome, encompassing 515 microbial genera (e.g., Methanobacterium) and 417 microbial KEGG genes (e.g., K00856—adenosine kinase). The temporally stable core microbiome profiles collected from all timepoints were strongly associated with production traits with substantial economic and environmental impact (e.g., average daily gain, daily feed intake, and methane emissions); 515 microbial genera explained 45–83%, and 417 microbial genes explained 44–83% of their phenotypic variation. Microbiome profiles influenced by the bovine genome explained 54–87% of the genetic variation of bovine traits. Overall, our results provide evidence that the temporally stable core microbiome identified can accurately predict host performance traits at phenotypic and genetic level based on a single timepoint sample taken as early as 7 months prior to slaughter.

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A One Health Perspective on Salmonella enterica Serovar Infantis, an Emerging Human Multidrug-Resistant Pathogen

April 2024

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51 Reads

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19 Citations

Emerging Infectious Diseases

Salmonella enterica serovar Infantis presents an ever-increasing threat to public health because of its spread throughout many countries and association with high levels of antimicrobial resistance (AMR). We analyzed whole-genome sequences of 5,284 Salmonella Infantis strains from 74 countries, isolated during 1989-2020 from a wide variety of human, animal, and food sources, to compare genetic phylogeny, AMR determinants, and plasmid presence. The global Salmonella Infantis population structure diverged into 3 clusters: a North American cluster, a European cluster, and a global cluster. The levels of AMR varied by Salmonella Infantis cluster and by isolation source; 73% of poultry isolates were multidrug resistant, compared with 35% of human isolates. This finding correlated with the presence of the pESI megaplasmid; 71% of poultry isolates contained pESI, compared with 32% of human isolates. This study provides key information for public health teams engaged in reducing the spread of this pathogen.


Fig. 1 Longitudinal growth rates (ADG) at different 4-week stages during the finishing period. a Variation in the growth curves from 10 randomly selected animals in the study. b Phenotypic distribution (after correction for systematic effects) of ADG 1 , ADG 2 , ADG 3 and ADG 4 , with decreasing means (1.57, 1.50, 1.48 and 1.41 kg/day, respectively). c Heritabilities, genomic and environmental correlations between ADG 1 , ADG 2 , ADG 3 and ADG 4
Including microbiome information in a multi-trait genomic evaluation: a case study on longitudinal growth performance in beef cattle

March 2024

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147 Reads

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3 Citations

Genetics Selection Evolution

Background Growth rate is an important component of feed conversion efficiency in cattle and varies across the different stages of the finishing period. The metabolic effect of the rumen microbiome is essential for cattle growth, and investigating the genomic and microbial factors that underlie this temporal variation can help maximize feed conversion efficiency at each growth stage. Results By analysing longitudinal body weights during the finishing period and genomic and metagenomic data from 359 beef cattle, our study demonstrates that the influence of the host genome on the functional rumen microbiome contributes to the temporal variation in average daily gain (ADG) in different months (ADG 1 , ADG 2 , ADG 3 , ADG 4 ). Five hundred and thirty-three additive log-ratio transformed microbial genes ( alr -MG) had non-zero genomic correlations (r g ) with at least one ADG-trait (ranging from |0.21| to |0.42|). Only a few alr -MG correlated with more than one ADG-trait, which suggests that a differential host-microbiome determinism underlies ADG at different stages. These alr -MG were involved in ribosomal biosynthesis, energy processes, sulphur and aminoacid metabolism and transport, or lipopolysaccharide signalling, among others. We selected two alternative subsets of 32 alr -MG that had a non-uniform or a uniform r g sign with all the ADG-traits, regardless of the r g magnitude, and used them to develop a microbiome-driven breeding strategy based on alr -MG only, or combined with ADG-traits, which was aimed at shaping the rumen microbiome towards increased ADG at all finishing stages. Combining alr -MG information with ADG records increased prediction accuracy of genomic estimated breeding values (GEBV) by 11 to 22% relative to the direct breeding strategy (using ADG-traits only), whereas using microbiome information, only, achieved lower accuracies (from 7 to 41%). Predicted selection responses varied consistently with accuracies. Restricting alr -MG based on their r g sign (uniform subset) did not yield a gain in the predicted response compared to the non-uniform subset, which is explained by the absence of alr -MG showing non-zero r g at least with more than one of the ADG-traits. Conclusions Our work sheds light on the role of the microbial metabolism in the growth trajectory of beef cattle at the genomic level and provides insights into the potential benefits of using microbiome information in future genomic breeding programs to accurately estimate GEBV and increase ADG at each finishing stage in beef cattle.


Microbiome-based cattle breeding: Improving the beef fatty acid profile and reducing methane output

August 2023

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42 Reads

Dietary n-3 fatty acids have many health benefits for humans, but beef products have less of them compared to fish. But this situation is not immutable. Fatty acids are primarily produced by bacteria which are influenced by cows' diet and genetics. So, researchers examined the possibility of breeding cattle based on microbiome traits for a better fatty acid profile in their meat and identified a set of bacterial genes that could be used in such a breeding program. First, they identified genes from ruminal bacteria that are influenced by host genetics. They then determined which of these potentially heritable microbial genes also correlated with a favorable meat fatty acid profile. Further analysis found that this set of microbial genes also corresponded to reduced methane output, meaning that a breeding program based on these microbial genes could both improve the fatty acid profiles and reduce greenhouse gas emissions. While data from a larger group of animals and more direct trials are needed, this study suggests that microbiome-based livestock breeding strategies could be used to improve microbiome-related traits.


KOunt-A reproducible KEGG orthologue abundance workflow

August 2023

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21 Reads

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3 Citations

Bioinformatics

Accurate gene prediction is essential for successful metagenome analysis. We present KOunt, a Snakemake pipeline, that precisely quantifies KEGG orthologue abundance. Availability and implementation: KOunt is available on GitHub: https://github.com/WatsonLab/KOunt. The KOunt reference database is available on figshare: https://doi.org/10.6084/m9.figshare.21269715. Test data are available at https://doi.org/10.6084/m9.figshare.22250152 and version 1.2.0 of KOunt at https://doi.org/10.6084/m9.figshare.23607834. Supplementary information: Supplementary data are available at Bioinformatics online.


Figure 1 Frequency of S. Infantis from each country Heatmap of the number of S. Infantis strains included in the dataset from each country
Salmonella Infantis, the emerging human multidrug resistant pathogen – a One Health perspective

July 2023

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263 Reads

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1 Citation

Salmonell a Infantis presents an ever-increasing threat to public health due to its spread throughout many countries and association with high levels of antimicrobial resistance (AMR). Whole genome sequences of 5,284 S . Infantis strains from 74 countries, isolated between 1989 and 2020 from a wide variety of sources including humans, animals, and food, were analysed to compare genetic phylogeny, AMR determinants and plasmid presence. The global S . Infantis population structure diverged into three clusters: a North American cluster, European cluster and a global cluster. The levels of AMR varied between the S . Infantis clusters and by isolation source; 73% of poultry isolates had multidrug resistance (MDR) compared to 35% of human isolates. This correlated with plasmid of emerging S . Infantis (pESI) presence; 71% of poultry isolates contained pESI versus 32% of human isolates. This provides important information for public health teams engaged in reducing the spread of this pathogen.


Systematic Review of Protein Biomarkers in Adult Patients With Chronic Rhinosinusitis

July 2023

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44 Reads

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9 Citations

American Journal of Rhinology and Allergy

Background: Chronic rhinosinusitis (CRS) is a heterogeneous condition characterized by differing inflammatory endotypes. The identification of suitable biomarkers could enable personalized approaches to treatment selection. Objective: This study aimed to identify and summarize clinical studies of biomarkers in adults with CRS in order to inform future research into CRS endotypes. Methods: We conducted systematic searches of MEDLINE and Web of Science from inception to January 30, 2022 and included all clinical studies of adult CRS patients and healthy controls measuring biomarkers using enzyme-linked immunosorbent assays or Luminex immunoassays. Outcomes included the name and tissue type of identified biomarkers and expression patterns within CRS phenotypes. Study quality was assessed using the National Institutes of Health quality assessment tool for observational cohort and cross-sectional studies. A narrative synthesis was performed. Results: We identified 78 relevant studies involving up to 9394 patients, predominantly with CRS with nasal polyposis. Studies identified 80 biomarkers from nasal tissue, 25 from nasal secretions, 14 from nasal lavage fluid, 24 from serum, and one from urine. The majority of biomarkers found to distinguish CRS phenotypes were identified in nasal tissue, especially in nasal polyps. Serum biomarkers were more commonly found to differentiate CRS from controls. The most frequently measured biomarker was IL-5, followed by IL-13 and IL-4. Serum IgE, IL-17, pentraxin-3 and nasal phospho-janus kinase 2, IL-5, IL-6, IL-17A, granulocyte-colony stimulating factor, and interferon gamma were identified as correlated with disease severity. Conclusion: We have identified numerous potential biomarkers to differentiate a range of CRS phenotypes. Future studies should focus on the prognostic role of nasal tissue biomarkers or expand on the more limited studies of nasal secretions and nasal lavage fluid.We registered this study in PROSPERO (CRD42022302787).


A comparison of single- and multi-coverage metagenomic binning
a, Hypothetical example using simulated data demonstrating our hypothesis that contigs from two different genomes may only be co-abundant in a single-sample and therefore may be mistakenly binned together in single-coverage binning. b, A comparison of completeness and contamination statistics for single-coverage bins (top row) and multi-coverage bins (bottom row). c, The number of bins produced by single- and multi-coverage binning. d, Violin plot of the mean pairwise inter-contig correlations for single- (n = 931) and multi-coverage bins (n = 1,660). The box plot center represents the median, the box the 25th and 75th percentiles and the whiskers 1.5× the interquartile range. e, Violin plot of the minimum pairwise inter-contig correlations for single- (n = 931) and multi-coverage bins (n = 1,660). The box plot center represents the median, the box the 25th and 75th percentiles and the whiskers 1.5× the interquartile range. f, Scatter plot of the percentage of pairwise inter-contig correlations below r = 0.5 for single- and multi-coverage bins.
The worst-performing single-coverage bin according to the mean pairwise correlation coefficient
a, Heat map of the worst single-coverage bin, showing the coverage of every contig (rows) in each sample (columns). Darker grey represent low coverage and lighter grey represent high coverage. Contaminant contigs, identified as having an r ≤ 0.9 with more than 90% of the contigs in the bin, are indicated to the right of the heat map. b, Line plot showing the coverage profile of the core (noncontaminant) contigs. c, Line plot showing the coverage profile of the contaminant contigs.
A comparison of single-coverage and multi-coverage metagenomic binning reveals extensive hidden contamination

June 2023

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145 Reads

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24 Citations

Nature Methods

Metagenomic binning has revolutionized the study of uncultured microorganisms. Here we compare single- and multi-coverage binning on the same set of samples, and demonstrate that multi-coverage binning produces better results than single-coverage binning and identifies contaminant contigs and chimeric bins that other approaches miss. While resource expensive, multi-coverage binning is a superior approach and should always be performed over single-coverage binning.


KOunt – A reproducible KEGG orthologue abundance workflow

April 2023

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95 Reads

Accurate gene prediction is essential for successful metagenome analysis. We present KOunt, a Snake-make pipeline, that precisely quantifies KEGG orthologue abundance. Availability and implementation KOunt is available on GitHub: https://github.com/WatsonLab/KOunt . The KOunt reference database is available on figshare: https://figshare.com/s/72fe3ed7dfbbdcd8b1e5 . Test data are available at https://figshare.com/ndownloader/files/39545968 and version 1.1.0 of KOunt at https://figshare.com/ndown-loader/files/39547273 . Contact jennifer.mattock@roslin.ed.ac.uk Supplementary information Supplementary data are available at Bioinformatics online.



Citations (11)


... The emergence of antimicrobial resistance (AMR) among NTS is concerning as it increases the morbidity, mortality, and cost of treatments (Salam et al., 2023). An increase in antimicrobial-resistant S. Infantis has been detected globally (Mejia et al., 2021;Mattock et al., 2024), including resistance to critically important third-generation cephalosporins and quinolones (Alvarez et al., 2023). Recently, a rise in multidrug resistance (MDR) among S. Infantis isolates has been described, which was linked with the emergence of an IncFIB-like plasmid commonly referred to as the 'plasmid of emerging S. enterica Infantis' (pESI). ...

Reference:

Monitoring antimicrobial resistance in Salmonella enterica serovar Infantis isolates of poultry, livestock, and humans across the United States, 2013–2020
A One Health Perspective on Salmonella enterica Serovar Infantis, an Emerging Human Multidrug-Resistant Pathogen
  • Citing Article
  • April 2024

Emerging Infectious Diseases

... The associations of gut microbiota with health and production performance have been extensively studied in livestock animals including donkeys [15][16][17][18], horses [19][20][21][22][23], cattle [24][25][26][27][28][29], buffalo [30][31][32], pigs [33,34], sheep and goats [5,[35][36][37][38][39][40][41][42]. The growth performance of livestock is directly related to the economic benefits of farming. ...

Including microbiome information in a multi-trait genomic evaluation: a case study on longitudinal growth performance in beef cattle

Genetics Selection Evolution

... Average nucleotide identity (ANI) was also computed using pyANI [78] with the blast method, and the ANI values shown reflect the percentage over the aligned regions. The presence of metabolic modules, including predicted antibiotic resistance pathways, was estimated using anvi-estimatemetabolism; based on KEGG pathways [79]. Antibiotic resistance was estimated with AMRFinderPlus using the K. pneumoniae model (Additional file 1: Table S13 and S14) [80]. ...

KOunt-A reproducible KEGG orthologue abundance workflow

Bioinformatics

... MDR S. Infantis strains isolated in broilers have been registered in different countries, such as Hungary, Germany, Italy, the Netherlands, Russia, and the United States [3]. Recent studies highlight that 70% of S. Infantis isolated from broiler meats in EU member states in 2016 were MDR [10]. The study focuses on the analysis of S. Infantis strains, showing a particular phenotype (lacking somatic antigen), isolated during a four-year period between 2018 and 2022 in the Apulia and Basilicata regions (South Italy). ...

Salmonella Infantis, the emerging human multidrug resistant pathogen – a One Health perspective

... I will employ 16S rRNA sequencing to assess bacterial communities and ITS sequencing to analyse fungal communities in the nasal microbiome. Blood samples will be analysed to measure immunological markers which are relevant to allergic and inflammatory responses (Gokani et al., 2023;Wang et al., 2023). ...

Systematic Review of Protein Biomarkers in Adult Patients With Chronic Rhinosinusitis
  • Citing Article
  • July 2023

American Journal of Rhinology and Allergy

... Recent studies have shown that there are significant differences in the intestinal microbiotas of local Chinese pig breeds and commercialized breeds 13 . Metagenomic binning approaches were applied in oral microbiome research and superior approach such as multi-coverage binning strategy was also applied to retrieve more comprehensive binning results 14,15 . In addition to updating data analysis pipelines, the microfluidics-based mini-metagenomics strategy could also be a powerful tool for dissecting microbial community structure in complex habitats 16 www.nature.com/scientificdata ...

A comparison of single-coverage and multi-coverage metagenomic binning reveals extensive hidden contamination

Nature Methods

... If rumen microbiome profiles are indeed temporally stable at taxonomic and functional levels, a single sample could be representative of the growing-finishing period, reinforcing results from previous investigations. Additionally, the possibility of using earlier samples to characterize the rumen microbiome would be advantageous, for example, to improve the annual gain of microbiome-driven breeding as developed by Martínez-Álvaro et al. 26 , as a result of faster genetic turnover. ...

Correction: Microbiome-driven breeding strategy potentially improves beef fatty acid profile benefiting human health and reduces methane emissions

... Additionally, the phenotypic associations observed between BGT and ruminal or gut microbiome composition extend to the genetic level. Genetic correlations between BGT and ruminal microbiome composition have been estimated in cattle (Martínez-Álvaro et al., 2022;Roehe et al., 2016;Saborío-Montero et al., 2020, as well as with gut microbiome composition in swine (Aliakbari et al., 2021). The association could be due to shared genetic architecture but also recursive effects at the phenotypic level (Saborío-Montero et al., 2021;Tiezzi et al., 2021;Valente et al., 2013). ...

Microbiome-driven breeding strategy potentially improves beef fatty acid profile benefiting human health and reduces methane emissions

... Higher levels have been observed in Japan at 72.2% of isolates from ground chicken, and 84% of broilers in Ecuador (5,6). AMR in S. Infantis varies by location; in South Africa only 13.4% of 387 S. Infantis isolates from humans had AMR (7). Conversely, in EU member states in 2016, 70% of S. ...

Genetic characterization of Salmonella Infantis from South Africa, 2004–2016

Access Microbiology

... A.baumannii is one of the most common and resistant hospital-acquired infection pathogens; once an individual is infected, it is difficult to remove AB infection. 14 The occurrence of CR-AB, MDR-AB and XDR-AB clinical isolates are becoming major threats to human health, 1,7,11 and it is difficult to achieve the desired results regarding controlling the CR-AB, MDR-AB and XDR-AB stains in an ICU, 11,14 which may be related to the insufficient regulation of antibiotic use. 5,6 Various studies have shown that the DDD of antibiotic consumption is linked to the incremental resistance rates of AB in hospitals, and nosocomial transmission of drug-resistant AB has been linked to environmental contamination and invasive procedures in ICUs. ...

Diversity of carbapenem-resistant Acinetobacter baumannii and bacteriophage-mediated spread of the Oxa23 carbapenemase

Microbial Genomics