Machine learning and statistics shape a novel path in archaeal promoter annotation

Background

Archaea are a vast and unexplored domain. Bioinformatic techniques might enlighten the path to a higher quality genome annotation in varied organisms. Promoter sequences of archaea have the action of a plethora of proteins upon it. The conservation found in a structural level of the binding site of proteins such as TBP, TFB, and TFE aids RNAP-DNA stabilization and makes the archaeal promoter prone to be explored by statistical and machine learning techniques.

Results and discussions

In this study, experimentally verified promoter sequences of the organisms Haloferax volcanii, Sulfolobus solfataricus, and Thermococcus kodakarensis were converted into DNA duplex stability attributes (i.e. numerical variables) and were classified through Artificial Neural Networks and an in-house statistical method of classification, being tested with three forms of controls. The recognition of these promoters enabled its use to validate unannotated promoter sequences in other organisms. As a result, the binding site of basal transcription factors was located through a DNA duplex stability codification. Additionally, the classification presented satisfactory results (above 90%) among varied levels of control.

Concluding remarks

The classification models were employed to perform genomic annotation into the archaea Aciduliprofundum boonei and Thermofilum pendens, from which potential promoters have been identified and uploaded into public repositories.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-022-04714-x.

Characterization of promoters in archaeal genomes based on DNA structural parameters

The transcription machinery of archaea can be roughly classified as a simplified version of eukaryotic organisms. The basal transcription factor machinery binds to the TATA box found around 28 nucleotides upstream of the transcription start site; however, some transcription units lack a clear TATA box and still have TBP/TFB binding over them. This apparent absence of conserved sequences could be a consequence of sequence divergence associated with the upstream region, operon, and gene organization. Furthermore, earlier studies have found that a structural analysis gains more information compared with a simple sequence inspection. In this work, we evaluated and coded 3630 archaeal promoter sequences of three organisms, Haloferax volcanii, Thermococcus kodakarensis, and Sulfolobus solfataricus into DNA duplex stability, enthalpy, curvature, and bendability parameters. We also split our dataset into conserved TATA and degenerated TATA promoters to identify differences among these two classes of promoters. The structural analysis reveals variations in archaeal promoter architecture, that is, a distinctive signal is observed in the TFB, TBP, and TFE binding sites independently of these being TATA-conserved or TATA-degenerated. In addition, the promoter encountering method was validated with upstream regions of 13 other archaea, suggesting that there might be promoter sequences among them. Therefore, we suggest a novel method for locating promoters within the genome of archaea based on DNA energetic/structural features.

DNA structural and physical properties reveal peculiarities in promoter sequences of the bacterium Escherichia coli K-12

The gene transcription of bacteria starts with a promoter sequence being recognized by a transcription factor found in the RNAP enzyme, this process is assisted through the conservation of nucleotides as well as other factors governing these intergenic regions. Faced with this, the coding of genetic information into physical aspects of the DNA such as enthalpy, stability, and base-pair stacking could suggest promoter activity as well as protrude differentiation of promoter and non-promoter data. In this work, a total of 3131 promoter sequences associated to six different sigma factors in the bacterium E. coli were converted into numeric attributes, a strong set of control sequences referring to a shuffled version of the original sequences as well as coding regions is provided. Then, the parameterized genetic information was normalized, exhaustively analyzed through statistical tests. The results suggest that strong signals in the promoter sequences match the binding site of transcription factor proteins, indicating that promoter activity is well represented by its conversion into physical attributes. Moreover, the features tested in this report conveyed significant variances between promoter and control data, enabling these features to be employed in bacterial promoter classification. The results produced here may aid in bacterial promoter recognition by providing a robust set of biological inferences.

DNA sequence, physics, and promoter function: Analysis of high-throughput data On T7 promoter variants activity

RNA polymerase/promoter recognition represents a basic problem of molecular biology. Decades-long efforts were made in the area, and yet certain challenges persist. The usage of certain most suitable model subjects is pivotal for the research. System of T7 bacteriophage RNA-polymerase/T7 native promoter represents an exceptional example for the purpose. Moreover, it has been studied the most and successfully applied to aims of biotechnology and bioengineering. Both structural simplicity and high specificity of this molecular duo are the reason for this. Despite highly similar sequences of distinct T7 native promoters, the T7 RNA-polymerase enzyme is capable of binding respective promoter in a highly specific and adjustable manner. One explanation here is that the process relies primarily on DNA physical properties rather than nucleotide sequence. Here, we address the issue by analyzing massive data recently published by Komura and colleagues. This initial study employed Next Generation Sequencing (NGS) in order to quantify activity of promoter variants including ones with multiple substitutions. As a result of our work substantial bias in simultaneous occurrence of single-nucleotide sequence alterations was found: the highest rate of co-occurrence was evidenced within specificity loop of binding region while the lowest - in initiation region of promoter. If both location and a kind of nucleotides involved in replacement (both initial and resulting) are taken into consideration, one can easily note that N to A substitutions are most preferred ones across the whole 19 b.p.-long sequence. At the same time, N to C are tolerated only at crucial position in recognition loop of binding region, and N to G are uniformly least tolerable. Later in this work the complete set of variants was split into groups with mutations (1) exclusively in binding region; (2) exclusively in melting region; (3) in both regions. Among these three groups second comprises extremely few variants (at triple-digit rate lesser than in two other groups, 46 versus over one and six thousand). Yet these are all promoter with substantial to high activity. This group two appeared heterogenous by primary sequence; indeed, upon further subdivision into above versus below average activity subgroups first one was found to comprise promoters with negligible conservation at -2 position of melting region; the second was hardly conserved in this region at all. This draws our attention to perfect consensus sequence of class III T7 promoter with -2 nucleotide randomized (all four are present by one to several copies in the previously published source dataset), the picture becomes even more pronounced. We therefore suggest that mutations at the position therefore do not cause significant changes in terms of promoter activity. At the same time, such modifications dramatically change DNA physical properties which were calculated in our study (namely electrostatic potential and propensity to bend). One possible suggestion here is that -2 nucleotide might function as a generic switch; if so, substitution -2A to -2T has important regulatory consequences. The fact that that -2 b.p. is the most evidently different nucleotide between class II versus class III promoters of T7 genome and that it also distinguishes the class III promoter in T7 genome versus promoters of its relative but reproductively isolated bacteriophage T3. In other words, it appears feasible that mutation at -2 nucleotide does not impede promoter activity yet alter its physical properties thus affecting differential RNA polymerase/promoter interaction.

Ideas and methods of nonlinear mathematics and theoretical physics in DNA science: the McLaughlin-Scott equation and its application to study the DNA open state dynamics

The review is devoted to a new and rapidly developing area related to the application of ideas and methods of nonlinear mathematics and theoretical physics to study the internal dynamics of DNA and, in particular, the behavior of the open states of DNA. There are two main competing approaches to this research. The first approach is based on the molecular dynamics method, which takes into account the motions of all structural elements of the DNA molecule and all interactions between them. The second approach is based on prior selection of the main (dominant) motions and their mathematical description using a small number of model equations. This review describes the results of the study of the open states of DNA performed within the framework of the second approach using the McLaughlin-Scott equation. We present the results obtained both in the case of homogeneous sequences: poly (A), poly (T), poly (G) and poly (C), and in the inhomogeneous case when the McLaughlin-Scott equation has been used for studying the dynamics of open states activated in the promoters A1, A2 and A3 of the bacteriophage T7 genome, in the genes IFNA17, ADRB2, NOS1 and IL-5, in the pBR322 and pTTQ18 plasmids. Particular attention is paid to the results concerning the effect of various external fields on the behavior of open states. In the concluding part of the review, new possibilities and prospects for the development of the considered approach and especially of the McLaughlin-Scott equation are discussed.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s12551-021-00801-0.