• Dr. Ahmed Ouali, 1948–2020

      GAGAOUA, Mohammed; Sentandreu, Miguel Angel; Coulis, Gérald; Aubry, Laurent; Astruc, Thierry; Herrera-Mendez, Carlos; Valin, Christian; Benyamin, Yves; Fernandez, Eric; Gaillard-Martinie, Brigitte; et al. (Elsevier BV, 2020-09)
    • Meta-proteomics for the discovery of protein biomarkers of beef tenderness: An overview of integrated studies

      Picard, Brigitte; Gagaoua, Mohammed; Marie Skłodowska-Curie Grant; Enterprise Ireland; Pôle Aquitain Agro-Alimentation et Nutrition; National Institute of Agronomical Research; National Institute of Origin and Quality; FNADT Massif Central; DATAR Massif Central; ANR GenAnimal; et al. (Elsevier BV, 2020-01)
      This meta-proteomics review focused on proteins identified as candidate biomarkers of beef tenderness by comparing extreme groups of tenderness using two-dimensional electrophoresis (2-DE) associated with mass spectrometry (MS). We reviewed in this integromics study the results of 12 experiments that identified protein biomarkers from two muscles, Longissimus thoracis (LT) and Semitendinosus (ST), of different types of cattle: young bulls, steers or cows from beef breeds (Charolais, Limousin, Blond d’Aquitaine), hardy breed (Salers) or mixed breed (PDO Maine-Anjou). Comparative proteomics of groups differing in their tenderness evaluated by instrumental Warner-Bratzler shear force (WBSF) or by sensory analysis using trained panelists, revealed 61 proteins differentially abundant (P < 0.05) between tender and tough groups. A higher number of discriminative proteins was observed for LT (50 proteins) compared to ST muscle (28 proteins). The Gene Ontology annotations showed that the proteins of structure and contraction, protection against oxidative stress and apoptosis, energy metabolism, 70 family HSPs and proteasome subunits are more involved in LT tenderness than in ST. Amongst the list of candidate biomarkers of tenderness some proteins such as HSPB1 are common between the 2 muscles whatever the evaluation method of tenderness, but some relationships with tenderness for others (MYH1, TNNT3, HSPB6) are inversed. Muscle specificities were revealed in this meta-proteomic study. For example, Parvalbumin (PVALB) appeared as a robust biomarker in ST muscle whatever the evaluation method of tenderness. HSPA1B seems to be a robust candidate for LT tenderness (with WBSF) regardless the animal type. Some gender specificities were further identified including similarities between cows and steers (MSRA and HSPA9) in contrast to bulls. The comparison of the 12 proteomic studies revealed strong dissimilarities to identify generic biomarkers of beef tenderness. This integrative analysis allowed better understanding of the biological processes involved in tenderness in two muscles and their variations according to the main factors underlying this quality. It allowed also proposing for the first time a comprehensive list of candidate biomarkers to be evaluated deeply to validate their relationships with tenderness on a large number of cattle and breeds.
    • Protein Array-Based Approach to Evaluate Biomarkers of Beef Tenderness and Marbling in Cows: Understanding of the Underlying Mechanisms and Prediction

      Gagaoua, Mohammed; Bonnet, Muriel; Picard, Brigitte; Pays de Loire Regional Council (MDPI AG, 2020-08-26)
      This study evaluated the potential of a panel of 20 protein biomarkers, quantified by Reverse Phase Protein Array (RPPA), to explain and predict two important meat quality traits, these being beef tenderness assessed by Warner–Bratzler shear force (WBSF) and the intramuscular fat (IMF) content (also termed marbling), in a large database of 188 Protected Designation of Origin (PDO) Maine-Anjou cows. Thus, the main objective was to move forward in the progression of biomarker-discovery for beef qualities by evaluating, at the same time for the two quality traits, a list of candidate proteins so far identified by proteomics and belonging to five interconnected biological pathways: (i) energy metabolic enzymes, (ii) heat shock proteins (HSPs), (iii) oxidative stress, (iv) structural proteins and (v) cell death and protein binding. Therefore, three statistical approaches were applied, these being Pearson correlations, unsupervised learning for the clustering of WBSF and IMF into quality classes, and Partial Least Squares regressions (PLS-R) to relate the phenotypes with the 20 biomarkers. Irrespective of the statistical method and quality trait, seven biomarkers were related with both WBSF and IMF, including three small HSPs (CRYAB, HSP20 and HSP27), two metabolic enzymes from the oxidative pathway (MDH1: Malate dehydrogenase and ALDH1A1: Retinal dehydrogenase 1), the structural protein MYH1 (Myosin heavy chain-IIx) and the multifunctional protein FHL1 (four and a half LIM domains 1). Further, three more proteins were retained for tenderness whatever the statistical method, among which two were structural proteins (MYL1: Myosin light chain 1/3 and TNNT1: Troponin T, slow skeletal muscle) and one was glycolytic enzyme (ENO3: β-enolase 3). For IMF, two proteins were, in this trial, specific for marbling whatever the statistical method: TRIM72 (Tripartite motif protein 72, negative) and PRDX6 (Peroxiredoxin 6, positive). From the 20 proteins, this trial allowed us to qualify 10 and 9 proteins respectively as strongly related with beef tenderness and marbling in PDO Maine-Anjou cows.
    • Proteomic biomarkers of beef colour

      Gagaoua, Mohammed; Hughes, Joanne; Terlouw, E.M. Claudia; Warner, Robyn D.; Purslow, Peter P.; Lorenzo, José M.; Picard, Brigitte; European Union; Enterprise Ireland; 713654; et al. (Elsevier BV, 2020-07)
      Background Implementation of proteomics over the last decade has been an important step toward a better understanding of the complex biological systems underlying the conversion of muscle to meat. These sophisticated analytical tools have helped to reveal the biochemical pathways involved in fresh meat colour and have identified key protein biomarkers. Scope and approach Until recently, there have been no detailed or critical studies on the role of protein biomarkers in determining meat colour. This review presents an integromics of recent muscle proteomic studies to investigate pathways and mechanisms of beef colour. A database was created from 13 independent proteomic-based studies including data on five muscles and a list of 79 proteins which were significantly correlated with colour traits. The database was subjected to a multistep analysis including Gene Ontology annotations, pathway analysis and literature mining. This report discusses the key protein biomarkers and the biological pathways associated with fresh beef colour. Biomarkers were prioritised by the frequency of identification and the need for future validation experiments is discussed. Key findings and conclusions This review identifies six pathways involved in beef colour including energy metabolism, heat shock and oxidative stress, myofibril structure, signalling, proteolysis and apoptosis. The data-mining of the list of the putative biomarkers showed that certain proteins, such as β-enolase (ENO3), Peroxiredoxin 6 (PRDX6), HSP27 (HSPB1), Phosphoglucomutase 1 (PGM1), Superoxide Dismutase [Cu-Zn] (SOD1) and μ-calpain (CAPN1) were consistently reported by multiple studies as being differentially expressed and having a significant role in beef colour. This integromics work proposes a list of 27 putative biomarkers of beef colour for validation using adapted high-throughput methods.
    • Proteomic biomarkers of beef colour

      Gagaoua, Mohammed; Hughes, Joanne; Terlouw, E.M. Claudia; Warner, Robyn D.; Purslow, Peter P.; Lorenzo, José M.; Picard, Brigitte; Marie Skłodowska-Curie grant agreement; Meat Technology Ireland; 713654; et al. (Elsevier, 2020-05-28)
      Background Implementation of proteomics over the last decade has been an important step toward a better understanding of the complex biological systems underlying the conversion of muscle to meat. These sophisticated analytical tools have helped to reveal the biochemical pathways involved in fresh meat colour and have identified key protein biomarkers. Scope and approach Until recently, there have been no detailed or critical studies on the role of protein biomarkers in determining meat colour. This review presents an integromics of recent muscle proteomic studies to investigate pathways and mechanisms of beef colour. A database was created from 13 independent proteomic-based studies including data on five muscles and a list of 79 proteins which were significantly correlated with colour traits. The database was subjected to a multistep analysis including Gene Ontology annotations, pathway analysis and literature mining. This report discusses the key protein biomarkers and the biological pathways associated with fresh beef colour. Biomarkers were prioritised by the frequency of identification and the need for future validation experiments is discussed. Key findings and conclusions This review identifies six pathways involved in beef colour including energy metabolism, heat shock and oxidative stress, myofibril structure, signalling, proteolysis and apoptosis. The data-mining of the list of the putative biomarkers showed that certain proteins, such as β-enolase (ENO3), Peroxiredoxin 6 (PRDX6), HSP27 (HSPB1), Phosphoglucomutase 1 (PGM1), Superoxide Dismutase [Cu-Zn] (SOD1) and μ-calpain (CAPN1) were consistently reported by multiple studies as being differentially expressed and having a significant role in beef colour. This integromics work proposes a list of 27 putative biomarkers of beef colour for validation using adapted high-throughput methods.
    • What are the drivers of beef sensory quality using metadata of intramuscular connective tissue, fatty acids and muscle fiber characteristics?

      Listrat, Anne; Gagaoua, Mohammed; Andueza, Donato; Gruffat, Dominique; Normand, Jérome; Mairesse, Guillaume; Picard, Brigitte; Hocquette, Jean-François; Agence de l'Environnement et de la Maîtrise de l'Energie, France; European Union; et al. (Elsevier BV, 2020-10)
      The aim of this integrative study was to investigate the relationships between biochemical traits (total, insoluble and soluble collagens (TCol, ICol, SCol), cross-links (CLs), proteoglycans (TPGs), proportion of fiber types, total lipids (TLips), main fatty acids (FAs) families, the n-6/n-3 polyunsaturated FA (n-6/n-3PUFA) ratio and the sensory attributes scores (tenderness, juiciness, flavor) of two muscles from beef: Rectus abdominis (RA) and Longissimus thoracis (LT). For robust analysis, a database was prepared using samples from three studies from animals raised under different production systems. The analyses were performed either on each study separately or on pooled data per muscle after removing as many experimental effects as possible in each study. The CLs (across the muscles and studies) and, to a lower extent, type IIA muscle fibers (mainly for RA muscles), saturated FAs (SFAs), monounsaturated FAs (MUFAs) (for the LT muscles) were the components the most frequently associated with tenderness. The CLs, type IIA muscle fibers (mainly for the RA muscles), TLips, SFAs, MUFAs, conjugated linoleic acids (CLAs) and n-6/n-3 PUFA ratio (mainly for the LT muscles) were the components the most associated with juiciness. The TLips and CLAs (across the muscles and studies), SFAs, MUFAs (mainly for the LT muscles), CLs (mainly for the RA muscles) and TPGs (mainly for the LT muscles) were the components the most associated with flavor liking. The CLs, CLAs, TLips, SFAs, MUFAs, n-6/n-3 PUFA ratio, type IIA and I muscle fibers were the components the most frequently associated with the 3 sensory scores taken together. The SCol, TPGs and type IIX+B muscle fibers were little associated with the sensory scores taken together. The TCol, ICol and PUFAs were components the least associated with sensory scores. The data of this integrative study highlighted for the first time that the CLs were negatively involved in the determination of the three sensory traits mainly in the RA muscle. The muscle fibers in this integrative study had a weak impact on the variations in beef sensory traits. The type IIA and IIX+B muscle fibers were respectively negatively and positively associated with tenderness, negatively associated with juiciness and flavor. The type I muscle fibers were overall positively associated with juiciness and flavor and negatively or positively with tenderness and these associations were muscle and study-dependent. Overall, the TLips and FAs were positively associated with the sensory scores and the n-6/n-3 PUFA ratio was negatively associated with them.
    • What are the drivers of beef sensory quality using metadata of intramuscular connective tissue, fatty acids and muscle fiber characteristics?

      Listrat, Anne; GAGAOUA, Mohammed; Andueza, Donato; Gruffat, Dominique; Normand, Jérome; Mairesse, Guillaume; Picard, Brigitte; Hocquette, Jean-François; Agence de l'Environnement et de la Maîtrise de l'Energie; European Union; et al. (Elsevier, 2020-08-14)
      The aim of this integrative study was to investigate the relationships between biochemical traits (total, insoluble and soluble collagens (TCol, ICol, SCol), cross-links (CLs), proteoglycans (TPGs), proportion of fiber types, total lipids (TLips), main fatty acids (FAs) families, the n-6/n-3 polyunsaturated FA (n-6/n-3PUFA) ratio and the sensory attributes scores (tenderness, juiciness, flavor) of two muscles from beef: Rectus abdominis (RA) and Longissimus thoracis (LT). For robust analysis, a database was prepared using samples from three studies from animals raised under different production systems. The analyses were performed either on each study separately or on pooled data per muscle after removing as many experimental effects as possible in each study. The CLs (across the muscles and studies) and, to a lower extent, type IIA muscle fibers (mainly for RA muscles), saturated FAs (SFAs), monounsaturated FAs (MUFAs) (for the LT muscles) were the components the most frequently associated with tenderness. The CLs, type IIA muscle fibers (mainly for the RA muscles), TLips, SFAs, MUFAs, conjugated linoleic acids (CLAs) and n-6/n-3 PUFA ratio (mainly for the LT muscles) were the components the most associated with juiciness. The TLips and CLAs (across the muscles and studies), SFAs, MUFAs (mainly for the LT muscles), CLs (mainly for the RA muscles) and TPGs (mainly for the LT muscles) were the components the most associated with flavor liking. The CLs, CLAs, TLips, SFAs, MUFAs, n-6/n-3 PUFA ratio, type IIA and I muscle fibers were the components the most frequently associated with the 3 sensory scores taken together. The SCol, TPGs and type IIX+B muscle fibers were little associated with the sensory scores taken together. The TCol, ICol and PUFAs were components the least associated with sensory scores. The data of this integrative study highlighted for the first time that the CLs were negatively involved in the determination of the three sensory traits mainly in the RA muscle. The muscle fibers in this integrative study had a weak impact on the variations in beef sensory traits. The type IIA and IIX+B muscle fibers were respectively negatively and positively associated with tenderness, negatively associated with juiciness and flavor. The type I muscle fibers were overall positively associated with juiciness and flavor and negatively or positively with tenderness and these associations were muscle and study-dependent. Overall, the TLips and FAs were positively associated with the sensory scores and the n-6/n-3 PUFA ratio was negatively associated with them.