Metabolic flux analysis of Branched-chain amino and keto acids (BCAA, BCKA) and β-Hydroxy β-methylbutyric acid (HMB) across multiple organs in the pig.

Author(s):  
Gabriella A.M. Ten Have ◽  
Lisa Jansen ◽  
Marieke G. Schooneman ◽  
Marielle P.K.J. Engelen ◽  
Nicolaas E.P. Deutz

Objective: Branched-chain amino acids (BCAA) and their metabolites the branched-chain keto acids (BCKA) and β-Hydroxy β-methylbutyric acid (HMB) are involved in the regulation of key signaling pathways in the anabolic response to a meal. However, their (inter)organ kinetics remain unclear. Therefore, BCAA (leucine (LEU), valine (VAL), isoleucine (ILE)), BCKA (α-ketoisocaproic acid (KIC), 3-methyl-2-oxovaleric acid (KMV), 2-oxoisovalerate (KIV)) and HMB across organ net fluxes were measured. Methods: In multi-catheterized pigs (n=12, ±25 kg), net fluxes across liver, portal drained viscera (PDV), kidney and hindquarter (HQ, muscle compartment) were measured before and 4h after bolus feeding of a complete meal (30% daily intake) in conscious state. Arterial and venous plasma were collected and concentrations were measured by LC- or GC-MS/MS. Data are expressed as mean[95%CI] and significance (p<0.05) from zero by Wilcoxon Signed Rank Test. Results: In the postabsorptive state (in nmol/kg bw/min), the kidney takes up HMB (3.2[1.3,5.0] ). BCKA is taken up by PDV (144[13,216]) but no release by other organs. In the postprandial state, the total net fluxes over 4h (in µmol/kg bw/4h) showed a release of all BCKA by HQ (46.2[34.2,58.2]), KIC by the PDV(12.3[7.0,17.6]) and KIV by the kidney(10.0[2.3,178]). HMB was released by the liver (0.76[0.49,1.0]). All BCKA were taken up by the liver (200[133,268]). Conclusions: Substantial differences are present in (inter)organ metabolism and transport among the BCAA and its metabolites BCKA and HMB. The presented data in a translation animal model are relevant for the future development of optimized clinical nutrition.

2020 ◽  
Vol 8 ◽  
Author(s):  
Ushashi Banerjee ◽  
Santhosh Sankar ◽  
Amit Singh ◽  
Nagasuma Chandra

Tuberculosis is one of the deadliest infectious diseases worldwide and the prevalence of latent tuberculosis acts as a huge roadblock in the global effort to eradicate tuberculosis. Most of the currently available anti-tubercular drugs act against the actively replicating form of Mycobacterium tuberculosis (Mtb), and are not effective against the non-replicating dormant form present in latent tuberculosis. With about 30% of the global population harboring latent tuberculosis and the requirement for prolonged treatment duration with the available drugs in such cases, the rate of adherence and successful completion of therapy is low. This necessitates the discovery of new drugs effective against latent tuberculosis. In this work, we have employed a combination of bioinformatics and chemoinformatics approaches to identify potential targets and lead candidates against latent tuberculosis. Our pipeline adopts transcriptome-integrated metabolic flux analysis combined with an analysis of a transcriptome-integrated protein-protein interaction network to identify perturbations in dormant Mtb which leads to a shortlist of 6 potential drug targets. We perform a further selection of the candidate targets and identify potential leads for 3 targets using a range of bioinformatics methods including structural modeling, binding site association and ligand fingerprint similarities. Put together, we identify potential new strategies for targeting latent tuberculosis, new candidate drug targets as well as important lead clues for drug design.


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