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Discovery of a novel lactate dehydrogenase tetramerization domain using epitope mapping and peptides.

ABSTRACT: Despite being initially regarded as a metabolic waste product, lactate is now considered to serve as a primary fuel for the tricarboxylic acid cycle in cancer cells. At the core of lactate metabolism, lactate dehydrogenases (LDHs) catalyze the interconversion of lactate to pyruvate and as such represent promising targets in cancer therapy. However, direct inhibition of the LDH active site is challenging from physicochemical and selectivity standpoints. However, LDHs are obligate tetramers. Thus, targeting the LDH tetrameric interface has emerged as an appealing strategy. In this work, we examine a dimeric construct of truncated human LDH to search for new druggable sites. We report the identification and characterization of a new cluster of interactions in the LDH tetrameric interface. Using nanoscale differential scanning fluorimetry, chemical denaturation, and mass photometry, we identified several residues (E62, D65, L71, and F72) essential for LDH tetrameric stability. Moreover, we report a family of peptide ligands based on this cluster of interactions. We next demonstrated these ligands to destabilize tetrameric LDHs through binding to this new tetrameric interface using nanoscale differential scanning fluorimetry, NMR water-ligand observed via gradient spectroscopy, and microscale thermophoresis. Altogether, this work provides new insights on the LDH tetrameric interface as well as valuable pharmacological tools for the development of LDH tetramer disruptors.

SUBMITTER: Thabault L

PROVIDER: S-EPMC8010463 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Autism spectrum disorder (ASD) is an important health issue and affects 1 in 59 children in the US. Prior studies determined that maternal autoantibody related (MAR) autism is thought to be associated with ~23% of ASD cases. We previously identified seven MAR-specific autoantigens including CRMP1, CRMP2, GDA, LDHA, LDHB, STIP1, and YBX1. We subsequently described the epitope peptide sequences recognized by maternal autoantibodies for each of the seven ASD-specific autoantigens. The aim of the current study was to expand upon our previous work and identify additional antigens recognized by the ASD-specific maternal autoantibodies, as well as to map the unique ASD-specific epitopes using microarray technology. Fetal Rhesus macaque brain tissues were separated by molecular weight and a fraction containing bands between 37 and 45 kDa was analyzed using 2-D gel electrophoresis, followed by peptide mass mapping using MALDI-TOF MS and TOF/TOF tandem MS/MS. Using this methodology, Neuron specific enolase (NSE) was identified as a target autoantigen and selected for epitope mapping. The full NSE sequence was translated into 15-mer peptides with an overlap of 14 amino acids onto microarray slides and probed with maternal plasma from mothers with an ASD child and from mothers with a Typically Developing child (TD) (ASD = 27 and TD = 21). The resulting data were analyzed by T-test. We found 16 ASD-specific NSE-peptide sequences for which four sequences were statistically significant (p < 0.05) using both the t-test and SAM t-test: DVAASEFYRDGKYDL (p = 0.047; SAM score 1.49), IEDPFDQDDWAAWSK (p = 0.049; SAM score 1.49), ERLAKYNQLMRIEEE (p = 0.045; SAM score 1.57), and RLAKYNQLMRIEEEL (p = 0.017; SAM score 1.82). We further identified 5 sequences that were recognized by both ASD and TD antibodies suggesting a large immunodominant epitope (DYPVVSIEDPFDQDDWAAW). While maternal autoantibodies against the NSE protein are present both in mothers with ASD and mothers of TD children, there are several ASD-specific epitopes that can potentially be used as MAR ASD biomarkers. Further, studies including analysis of NSE as a target protein in combination with the previously identified MAR ASD autoantigens are currently underway.

Project description:Human proteomic databases required for MS peptide identification are frequently updated and carefully curated, yet are still incomplete because it has been challenging to acquire every protein sequence from the diverse assemblage of proteoforms expressed in every tissue and cell type. In particular, alternative splicing has been shown to be a major source of this cell-specific proteomic variation. Many new alternative splice forms have been detected at the transcript level using next generation sequencing methods, especially RNA-Seq, but it is not known how many of these transcripts are being translated. Leveraging the unprecedented capabilities of next generation sequencing methods, we collected RNA-Seq and proteomics data from the same cell population (Jurkat cells) and created a bioinformatics pipeline that builds customized databases for the discovery of novel splice-junction peptides. Eighty million paired-end Illumina reads and ?500,000 tandem mass spectra were used to identify 12,873 transcripts (19,320 including isoforms) and 6810 proteins. We developed a bioinformatics workflow to retrieve high-confidence, novel splice junction sequences from the RNA data, translate these sequences into the analogous polypeptide sequence, and create a customized splice junction database for MS searching. Based on the RefSeq gene models, we detected 136,123 annotated and 144,818 unannotated transcript junctions. Of those, 24,834 unannotated junctions passed various quality filters (e.g. minimum read depth) and these entries were translated into 33,589 polypeptide sequences and used for database searching. We discovered 57 splice junction peptides not present in the Uniprot-Trembl proteomic database comprising an array of different splicing events, including skipped exons, alternative donors and acceptors, and noncanonical transcriptional start sites. To our knowledge this is the first example of using sample-specific RNA-Seq data to create a splice-junction database and discover new peptides resulting from alternative splicing.

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Discovery of a novel lactate dehydrogenase tetramerization domain using epitope mapping and peptides.

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