Single-molecule chromatin fiber sequencing is based on the single-nucleotide resolution identification of DNA N6-methyladenine (m6A) along individual sequencing reads. We present fibertools, a semi-supervised convolutional neural network that permits the fast and accurate identification of both endogenous and exogenous m6A-marked bases using single-molecule long-read sequencing. Fibertools enables highly accurate (>90% precision and recall) m6A identification along multi-kilobase DNA molecules with a ~1,000-fold improvement in speed and the capacity to generalize to new sequencing chemistries.
Proline utilization A (PutA) are bifunctional enzymes. PutAs oxidize proline to glutamate via two 2‐electron oxidization steps at the spatially separated flavin‐dependent L‐proline dehydrogenase (PRODH) domain and NAD+‐dependent L‐glutamate‐γ‐ semialdehyde (GSAL) dehydrogenase (GSALDH) domain producing NADH at the same time. The evidence of flavin in the PRODH domain being reduced and covalently modified by thiazolidine‐2‐carboxylate (T2C) motivates us to further characterize the kinetic mechanism and explore potential substrates. This study characterized the kinetics of PutA from Sinorhizobium meliloti (SmPutA) using T2C and thioproline, a natural product, as substrates. The replacement of either C3 or C5 atom of proline by sulfur increases binding affinity significantly and the catalytic efficiency is 33‐fold or 10‐fold higher respectively. Consistently, the single turn‐over study also suggests T2C and thioproline reduce the flavin faster than proline. Interestingly, neither intermediate can be further catalyzed by the GSALDH and the mass spectrometry study suggests thioproline is oxidized and hydrolyzed to cysteine. Work is ongoing to determine the product from T2C and detailed mechanism of the slow inactivation of SmPutA by T2C.
Proline metabolism is critical for several cellular processes such as serving as carbon and nitrogen sources, preventing osmotic stress especially in plants, scavenging reactive oxygen species, and promoting pathogen virulence. In all organisms proline is oxidized into glutamate by the coordinated activities of the flavin‐dependent enzyme L‐proline dehydrogenase (PRODH) and NAD+‐dependent enzyme L‐glutamate‐γ‐semialdehyde (GSAL) dehydrogenase (GSALDH). In gram‐negative bacteria, these two enzymes are encoded on one polypeptide called proline utilization A (PutA). PutA from certain bacteria such as Escherichia coli (EcPutA), also includes a ribbon‐helix‐helix (RHH) DNA binding domain at the N‐terminus that is tethered to the PRODH domain by a 35 amino acid linker corresponding to residues 50–85 of the total 1320 in EcPutA. The RHH domain enables PutA to function as a transcription repressor of the put regulon (putP and putA genes) in addition to its enzymatic roles. This study aims to understand the role of the linker in the redox regulation of PutA and its functions. As conformational changes are required for PutA to switch between transcriptional repressor and enzymatic functions, the linker is proposed to be important for optimal arrangement of the RHH and PRODH domains. Partial and total linker deletion mutants, Δ50–73 EcPutA and Δ50–85 EcPutA, respectively, were characterized. Purified Δ50–85 EcPutA was shown to behave similarly to wild‐type PutA as assessed by enzyme activity and DNA binding assays. The Δ50–85 EcPutA mutant depleted of the full linker region, however, was unable to function as a transcription repressor in cell based assays indicating that the linker is necessary for EcPutA to bind to DNA in vivo. Work is ongoing to determine whether the transcription repressor activity of EcPutA is restored in partial linker mutant Δ50–73 EcPutA.
Support or Funding Information
NIH grants R01GM061068 and P30GM103335. Department of Biochemistry and Redox Biology Center, University of Nebraska‐Lincoln.
Model for regulation of put regulon.s
Domain structure and small angle X‐ray scattering model of EcPutA. Adapted from "Structure, function, and mechanism of proline," by L. Liu, J. J. Tanner, and D. F. Becker. 2017, Archives of Biochemistry and Biophysics, 632, p. 142. Copyright 2019 by 2019 Elsevier B.V.
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