Sequence Determination Research Articles

Predicting functional UTR variants by integrating region-specific features.

The untranslated region (UTR) of messenger ribonucleic acid (mRNA), including the 5'UTR and 3'UTR, plays a critical role in regulating gene expression and translation. Variants within the UTR can lead to changes associated with human traits and diseases; however, computational prediction of UTR variant effect is challenging. Current noncoding variant prediction mainly focuses on the promoters and enhancers, neglecting the unique sequence of the UTR and thereby limiting their predictive accuracy. In this study, using consolidated datasets of UTR variants from disease databases and large-scale experimental data, we systematically analyzed more than 50 region-specific features of UTR, including functional elements, secondary structure, sequence composition and site conservation. Our analysis reveals that certain features, such as C/G-related sequence composition in 5'UTR and A/T-related sequence composition in 3'UTR, effectively differentiate between nonfunctional and functional variant sets, unveiling potential sequence determinants of functional UTR variants. Leveraging these insights, we developed two classification models to predict functional UTR variants using machine learning, achieving an area under the curve (AUC) value of 0.94 for 5'UTR and 0.85 for 3'UTR, outperforming all existing methods. Our models will be valuable for enhancing clinical interpretation of genetic variants, facilitating the prediction and management of disease risk.

A high-throughput sequence determination for one cyclic peptide immobilized on a single bead by the one-pot cyanidation followed by MALDI-TOF-MS/MS for discovery of interacting peptides.

One cyclic peptide immobilized on one gel-type bead has been employed for the discovery of both interacting peptides and/or medicinal medium-sized molecules. Although high-throughput characterization of recognized peptides has been a bottleneck, here, we describe direct liberation from beads by a one-pot reaction using 2-nitro-5-thiocyanatobenzoic acid followed by mass spectrometry to realize faster and routine sequencing of the peptide on the beads. This is useful for the investigation of protein-protein interactions as well as discovery of drug candidates.

A predictive algorithm for the analysis of AMR trends and healthcare decision support

Background Translating available AMR surveillance data to observe evolving patterns of microbial resistance to antimicrobial agents while identifying regions at high risk of resistant cases and serving as a decision-support tool is an aspect of AMR surveillance that is rarely explored nationwide and uncommon globally. Therefore, we developed a two-tier dashboard algorithm (PATHFINDER) that can analyse antimicrobial surveillance datasets, observe evolving global spatiotemporal patterns of AMR, and integrate local AMR gene resources to identify functional AMR determinant genes and antibiotic classes from the query organism genome. Methods The Python-based plotly library was used to develop the interactive variables of the Antimicrobial Testing Leadership Surveillance (ATLAS) dataset in an adjustable spatiotemporal environment. A lightweight database containing multiple known resistant genes from the ResFinder database was used as a prototype to identify unique AMR determinant genes from query nucleotide sequences. In R, a function was created to accept query genome sequences and generate Kmers of length 250 using the blaster package. The GPT-4 API plug-in was embedded with adequate prompt parsing for it as an interpretation LLM function. Results AMR trendline plots were designed for invasive infections and customised based on the class of antibiotics and infection types on the surveillance dashboard. The decision-support tool correctly predicted resistant genes with a sensitivity of 75% on pre-confirmed organisms. The observed specificity score (51.5%) was due to the need for more filtering and optimisation and not to PATHFINDER performance. When run against the reference gene dataset containing pre-identified AMR genes, the support tool generated a BLAST table with identified AMR gene determinants in a nucleotide sequence. Conclusions The PATHFINDER algorithm has the potential to revolutionise healthcare decision-making. It can inform targeted interventions, guide antimicrobial stewardship efforts at a national level, promote appropriate antibiotic use, and significantly reduce the risk of resistance development.

Functional and antigenic characterization of SARS-CoV-2 spike fusion peptide by deep mutational scanning

The fusion peptide of SARS-CoV-2 spike protein is functionally important for membrane fusion during virus entry and is part of a broadly neutralizing epitope. However, sequence determinants at the fusion peptide and its adjacent regions for pathogenicity and antigenicity remain elusive. In this study, we perform a series of deep mutational scanning (DMS) experiments on an S2 region spanning the fusion peptide of authentic SARS-CoV-2 in different cell lines and in the presence of broadly neutralizing antibodies. We identify mutations at residue 813 of the spike protein that reduced TMPRSS2-mediated entry with decreased virulence. In addition, we show that an F823Y mutation, present in bat betacoronavirus HKU9 spike protein, confers resistance to broadly neutralizing antibodies. Our findings provide mechanistic insights into SARS-CoV-2 pathogenicity and also highlight a potential challenge in developing broadly protective S2-based coronavirus vaccines.

An integrated technology for quantitative wide mutational scanning of human antibody Fab libraries

Antibodies are engineerable quantities in medicine. Learning antibody molecular recognition would enable the in silico design of high affinity binders against nearly any proteinaceous surface. Yet, publicly available experiment antibody sequence-binding datasets may not contain the mutagenic, antigenic, or antibody sequence diversity necessary for deep learning approaches to capture molecular recognition. In part, this is because limited experimental platforms exist for assessing quantitative and simultaneous sequence-function relationships for multiple antibodies. Here we present MAGMA-seq, an integrated technology that combines multiple antigens and multiple antibodies and determines quantitative biophysical parameters using deep sequencing. We demonstrate MAGMA-seq on two pooled libraries comprising mutants of nine different human antibodies spanning light chain gene usage, CDR H3 length, and antigenic targets. We demonstrate the comprehensive mapping of potential antibody development pathways, sequence-binding relationships for multiple antibodies simultaneously, and identification of paratope sequence determinants for binding recognition for broadly neutralizing antibodies (bnAbs). MAGMA-seq enables rapid and scalable antibody engineering of multiple lead candidates because it can measure binding for mutants of many given parental antibodies in a single experiment.

Prevalence and genetic diversity of the <i>Alongshan virus (Flaviviridae)</i> circulating in ticks in the south of Eastern Siberia

Introduction. Tick-borne infections are of great importance for many regions of Russia, including Eastern Siberia. This unfavorable epidemiological situation can be characterized not only by the circulation of well-known tick-borne infections, but also by the identification of new pathogens, the role of which remains little or generally unexplored. Multicomponent flavi-like viruses can cause infectious diseases in humans and pose a threat to public health. The purpose of the study was the identification and molecular genetic characterization of the Alongshan virus (Flaviviridae, ALSV) isolates, transmitted by ticks in the south of Eastern Siberia. Materials and methods. Total 1060 ticks were collected and analyzed from the territory of the Republics of Khakassia, Tuva, Buryatia, Irkutsk Region and Transbaikal Territory (Zabaykalsky Krai) in the spring-summer period 2023. ALSV RNA was detected by RT-PCR followed by nucleotide sequence determination and phylogenetic analysis for each segment of the genome. Results. The ALSV infection rate in Ixodes persulcatus ticks collected in the Republic of Khakassia was 3.3% (95% CI: 1.4–7.5); in Irkutsk Oblast – 1.0% (95% CI: 0.3–3.7); in the Republic of Tuva – 0.9% (95% CI: 0.3–3.4) and in Transbaikal Krai – 0.7% (95% CI: 0.2–3.6). Sequences of all four segments of ALSV genetic variants circulating in I. persulcatus ticks in the south of Eastern Siberia are grouped with sequences found in China and clustered into the Asian subgroup transmitted by taiga ticks. The level of difference in the nucleotide sequences of genome fragments among the identified genetic variants of ALSV ranged from 2 to 3%. Conclusion. The article shows the widespread distribution of ALSV in I. persulcatus ticks in the Republics of Khakassia and Tyva, Irkutsk Oblast and Transbaikal Territory. The obtained data actualize monitoring of changes in the area of distribution of potentially dangerous for humans flavi-like viruses and their vectors.

Plasmid-mediated horizontal gene mobilisation: Insights from two lactococcal conjugative plasmids.

The distinct conjugation machineries encoded by plasmids pNP40 and pUC11B represent the most prevalent plasmid transfer systems among lactococcal strains. In the current study, we identified genetic determinants that underpin pNP40- and pUC11B-mediated, high-frequency mobilisation of other, non-conjugative plasmids. The mobilisation frequencies of the smaller, non-conjugative plasmids and the minimal sequences required for their mobilisation were determined, owing to the determination of the oriT sequences of both pNP40 and pUC11B, which allowed the identification of similar sequences in some of the non-conjugative plasmids that were shown to promote their mobilisation. Furthermore, the auxiliary gene mobC, two distinct functional homologues of which are present in several plasmids harboured by the pNP40- and pUC11B-carrying host strains, was observed to confer a high-frequency mobilisation phenotype. These findings provide mechanistic insights into how lactococcal conjugative plasmids achieve conjugation and promote mobilisation of non-conjugative plasmids. Ultimately, these insights would be harnessed to optimise conjugation and mobilisation strategies for the rapid and predictable development of robust and technologically improved strains.

Sequence basis of transcription initiation in the human genome.

Transcription initiation is a process that is essential to ensuring the proper function of any gene, yet we still lack a unified understanding of sequence patterns and rules that explain most transcription start sites in the human genome. By predicting transcription initiation at base-pair resolution from sequences with a deep learning-inspired explainable model called Puffin, we show that a small set of simple rules can explain transcription initiation at most human promoters. We identify key sequence patterns that contribute to human promoter activity, each activating transcription with distinct position-specific effects. Furthermore, we explain the sequence basis of bidirectional transcription at promoters, identify the links between promoter sequence and gene expression variation across cell types, and explore the conservation of sequence determinants of transcription initiation across mammalian species.

U-CAN-seq: A Universal Competition Assay by Nanopore Sequencing.

RNA viruses quickly evolve subtle genotypic changes that can have major impacts on viral fitness and host range, with potential consequences for human health. It is therefore important to understand the evolutionary fitness of novel viral variants relative to well-studied genotypes of epidemic viruses. Competition assays are an effective and rigorous system with which to assess the relative fitness of viral genotypes. However, it is challenging to quickly and cheaply distinguish and quantify fitness differences between very similar viral genotypes. Here, we describe a protocol for using reverse transcription PCR in combination with commercial nanopore sequencing services to perform competition assays on untagged RNA viruses. Our assay, called the Universal Competition Assay by Nanopore Sequencing (U-CAN-seq), is relatively cheap and highly sensitive. We used a well-studied N24A mutation in the chikungunya virus (CHIKV) nsp3 gene to confirm that we could detect a competitive disadvantage using U-CAN-seq. We also used this approach to show that mutations to the CHIKV 5' conserved sequence element that disrupt sequence but not structure did not affect the fitness of CHIKV. However, similar mutations to an adjacent CHIKV stem loop (SL3) did cause a fitness disadvantage compared to wild-type CHIKV, suggesting that structure-independent, primary sequence determinants in this loop play an important role in CHIKV biology. Our novel findings illustrate the utility of the U-CAN-seq competition assay.

A systemic approach to identifying sequence frameworks that decrease mAb production in a transient Chinese hamster ovary cell expression system.

Monoclonal antibodies (mAbs) are often engineered at the sequence level for improved clinical performance yet are rarely evaluated prior to candidate selection for their "developability" characteristics, namely expression, which can necessitate additional resource investments to improve the manufacturing processes for problematic mAbs. A strong relationship between primary sequence and expression has emerged, with slight differences in amino acid sequence resulting in titers differing by up to an order of magnitude. Previous work on these "difficult-to-express" (DTE) mAbs has shown that these phenotypes are driven by post-translational bottlenecks in antibody folding, assembly, and secretion processes. However, it has been difficult to translate these findings across cell lines and products. This work presents a systematic approach to study the impact of sequence variation on mAb expression at a larger scale and under more industrially relevant conditions. The analysis found 91 mutations that decreased transient expression of an IgG1κ in Chinese hamster ovary (CHO) cells and revealed that mutations at inaccessible residues, especially those leading to decreases in residue hydrophobicity, are not favorable for high expression. This workflow can be used to better understand sequence determinants of mAb expression to improve candidate selection procedures and reduce process development timelines.

Vertical differentiation drives the changes in the main microflora and metabolites of carbon and nitrogen cycling in the early freeze-thaw period in the Qinghai Lake Basin.

Global climate change has altered the frequency of soil freeze-thaw cycles, but the response of soil microorganisms to different elevation gradients during the early freeze-thaw period remains unclear. So far, the influence of the altitudinal gradient on the microbial community and metabolic characteristics in the early freeze-thaw period of the Qinghai Lake Basin remains unclear. To this end, we collected soil at different elevations in the early freeze-thaw period of the Qinghai Lake Basin and investigated the influence of the elevation gradient on soil microbial community characteristics and soil metabolic processes as well as the corresponding environmental driving mechanism by high-throughput sequencing and LC-MS (Liquid Chromatograph-Mass Spectrometer) nontargeted metabolite determination. The results showed that Proteobacteria were the dominant microflora in the Qinghai Lake Basin. The dominant phyla associated with carbon and nitrogen are Proteobacteria and Firmicutes, both of which are significantly affected by elevation. The soil physicochemical factors jointly affected the soil microbial communities and metabolism. Total phosphorus nitrate nitrogen and pH were the main driving factors of the microbial community, and metabolites were sensitive to changes in chemical factors. In short, the microbial community structure and function, soil physicochemical factors and soil metabolic processes were significantly affected by the altitudinal gradient in the early freeze-thaw period, while the microbial community diversity showed no significant response to the altitudinal gradient. Additionally, a high potassium content in the soil may promote the growth and reproduction of bacteria associated with carbon and nitrogen cycling, as well as the production of metabolites.

Associating protein sequence positions with the modulation of quantitative phenotypes

Although protein sequences encode the information for folding and function, understanding their link is not an easy task. Unluckily, the prediction of how specific amino acids contribute to these features is still considerably impaired. Here, we developed a simple algorithm that finds positions in a protein sequence with potential to modulate the studied quantitative phenotypes. From a few hundred protein sequences, we perform multiple sequence alignments, obtain the per-position pairwise differences for both the sequence and the observed phenotypes, and calculate the correlation between these last two quantities. We tested our methodology with four cases: archaeal Adenylate Kinases and the organisms optimal growth temperatures, microbial rhodopsins and their maximal absorption wavelengths, mammalian myoglobins and their muscular concentration, and inhibition of HIV protease clinical isolates by two different molecules. We found from 3 to 10 positions tightly associated with those phenotypes, depending on the studied case. We showed that these correlations appear using individual positions but an improvement is achieved when the most correlated positions are jointly analyzed. Noteworthy, we performed phenotype predictions using a simple linear model that links per-position divergences and differences in the observed phenotypes. Predictions are comparable to the state-of-art methodologies which, in most of the cases, are far more complex. All of the calculations are obtained at a very low information cost since the only input needed is a multiple sequence alignment of protein sequences with their associated quantitative phenotypes. The diversity of the explored systems makes our work a valuable tool to find sequence determinants of biological activity modulation and to predict various functional features for uncharacterized members of a protein family.

Whole-genome sequence and resistance determinants of four Elizabethkingia anophelis clinical isolates collected in Hanoi, Vietnam

Four isolates of the opportunistic pathogen Elizabethkingia anophelis were identified for the first time in a Vietnamese hospital and underwent antimicrobial susceptibility testing and genomic characterization by whole-genome sequencing. Complete, fully circularized genome sequences were obtained for all four isolates. Average Nucleotide Identity analysis and single nucleotide polymorphism phylogenetic analysis on the core genome showed that three of the four isolates were genetically distinct, ruling out the hypothesis of a single strain emergence. Antibiotic susceptibility testing highlighted multi-resistant phenotypes against most antimicrobial families, including beta-lactams, carbapenems, aminoglycosides, quinolones, macrolides, amphenicols, rifamycins and glycopeptides. Additionally, in silico genomic analysis was used to correlate the phenotypic susceptibility to putative resistance determinants, including resistance genes, point mutations and multidrug efflux pumps. Nine different resistance genes were located inside a single resistance pocket predicted to be a putative Integrative and Conjugative Element (ICE). This novel ICE was shared by three isolates from two different lineages and displayed similarity with ICEs previously reported in various Elizabethkingia and Chryseobacterium species. The role of such ICEs in pathogenicity, genome plasticity and antimicrobial resistance gene spread within the Flavobacteriaceae family needs to be further elucidated.

On Conic Equations Under Bernstein Operators

One of the most important problems in approximation theory in mathematical analysis is the determination of sequences of polynomials that converge to functions and have the same geometric properties. This type of approximation is called the shape-preserving approximation. These types of problems are usually handled depending on the convexity of the functions, the degree of smoothness depending on the order of differentiability, or whether it satisfies a functional equation. The problem addressed in this paper belongs to the third class. A quadratic bivariate algebraic equation denotes geometrically some well-known shapes such as circles, ellipses, hyperbolas and parabolas. Such equations are known as conic equations. In this study, it is investigated whether conic equations transform into a conic equation under bivariate Bernstein polynomials, and if so, which conic equation it transforms into.

Purine nucleosides replace cAMP in allosteric regulation of PKA in trypanosomatid pathogens.

Cyclic nucleotide binding domains (CNB) confer allosteric regulation by cAMP or cGMP to many signaling proteins, including PKA and PKG. PKA of phylogenetically distant Trypanosoma is the first exception as it is cyclic nucleotide-independent and responsive to nucleoside analogues (Bachmaier et al., 2019). Here, we show that natural nucleosides inosine, guanosine and adenosine are nanomolar affinity CNB ligands and activators of PKA orthologs of the important tropical pathogens Trypanosoma brucei, Trypanosoma cruzi, and Leishmania. The sequence and structural determinants of binding affinity, -specificity and kinase activation of PKAR were established by structure-activity relationship (SAR) analysis, co-crystal structures and mutagenesis. Substitution of two to three amino acids in the binding sites is sufficient for conversion of CNB domains from nucleoside to cyclic nucleotide specificity. In addition, a trypanosomatid-specific C-terminal helix (αD) is required for high affinity binding to CNB-B. The αD helix functions as a lid of the binding site that shields ligands from solvent. Selectivity of guanosine for CNB-B and of adenosine for CNB-A results in synergistic kinase activation at low nanomolar concentration. PKA pulldown from rapid lysis establishes guanosine as the predominant ligand in vivo in T. brucei bloodstream forms, whereas guanosine and adenosine seem to synergize in the procyclic developmental stage in the insect vector. We discuss the versatile use of CNB domains in evolution and recruitment of PKA for novel nucleoside-mediated signaling.

Purine nucleosides replace cAMP in allosteric regulation of PKA in trypanosomatid pathogens

Cyclic nucleotide binding domains (CNB) confer allosteric regulation by cAMP or cGMP to many signaling proteins, including PKA and PKG. PKA of phylogenetically distant Trypanosoma is the first exception as it is cyclic nucleotide-independent and responsive to nucleoside analogues (Bachmaier et al., 2019). Here, we show that natural nucleosides inosine, guanosine and adenosine are nanomolar affinity CNB ligands and activators of PKA orthologs of the important tropical pathogens Trypanosoma brucei, Trypanosoma cruzi, and Leishmania. The sequence and structural determinants of binding affinity, -specificity and kinase activation of PKAR were established by structure-activity relationship (SAR) analysis, co-crystal structures and mutagenesis. Substitution of two to three amino acids in the binding sites is sufficient for conversion of CNB domains from nucleoside to cyclic nucleotide specificity. In addition, a trypanosomatid-specific C-terminal helix (αD) is required for high affinity binding to CNB-B. The αD helix functions as a lid of the binding site that shields ligands from solvent. Selectivity of guanosine for CNB-B and of adenosine for CNB-A results in synergistic kinase activation at low nanomolar concentration. PKA pulldown from rapid lysis establishes guanosine as the predominant ligand in vivo in T. brucei bloodstream forms, whereas guanosine and adenosine seem to synergize in the procyclic developmental stage in the insect vector. We discuss the versatile use of CNB domains in evolution and recruitment of PKA for novel nucleoside-mediated signaling.

Sequence-structure-function characterization of the emerging tetracycline destructase family of antibiotic resistance enzymes

Tetracycline destructases (TDases) are flavin monooxygenases which can confer resistance to all generations of tetracycline antibiotics. The recent increase in the number and diversity of reported TDase sequences enables a deep investigation of the TDase sequence-structure-function landscape. Here, we evaluate the sequence determinants of TDase function through two complementary approaches: (1) constructing profile hidden Markov models to predict new TDases, and (2) using multiple sequence alignments to identify conserved positions important to protein function. Using the HMM-based approach we screened 50 high-scoring candidate sequences in Escherichia coli, leading to the discovery of 13 new TDases. The X-ray crystal structures of two new enzymes from Legionella species were determined, and the ability of anhydrotetracycline to inhibit their tetracycline-inactivating activity was confirmed. Using the MSA-based approach we identified 31 amino acid positions 100% conserved across all known TDase sequences. The roles of these positions were analyzed by alanine-scanning mutagenesis in two TDases, to study the impact on cell and in vitro activity, structure, and stability. These results expand the diversity of TDase sequences and provide valuable insights into the roles of important residues in TDases, and flavin monooxygenases more broadly.

Three‐dimensional Modeling of Ore‐forming Elements and Mineralization Prognosis for the Yechangping Mo Deposit, Henan Province, China

AbstractThree‐dimensional geochemical modeling of ore‐forming elements is crucial for predicting deep mineralization. This approach provides key information for the quantitative prediction of deep mineral localization, three‐dimensional fine interpolation, analysis of spatial distribution patterns, and extraction of quantitative mineral‐seeking markers. The Yechangping molybdenum (Mo) deposit is a significant and extensive porphyry‐skarn deposit in the East Qinling–Dabie Mo polymetallic metallogenic belt at the southern margin of the North China Block. Abundant borehole data on ore‐forming elements underpin deep geochemical predictions. The methodology includes the following steps: (1) Three‐dimensional geological modeling of the deposit was established. (2) Correlation, cluster, and factor analyses post delineation of mineralization stages and determination of mineral generation sequence to identify (Cu, Pb, Zn, Ag) and (Mo, W, mfe) assemblages. (3) A three‐dimensional geochemical block model was constructed for Mo, W, mfe, Cu, Zn, Pb, and Ag using the ordinary kriging method, and the variational function was developed. (4) Spatial distribution and enrichment characteristics analysis of ore‐forming elements are performed to extract geological information, employing the variogram and w(Cu + Pb + Zn + Ag)/w(Mo + W) as predictive indicators. (5) Identifying the western, northwestern, and southwestern areas of the mine with limited mineralization potential, contrasted by the northeastern and southeastern areas favorable for mineral exploration.

Borreliella burgdorferi factor H-binding proteins are not required for serum resistance and infection in mammals.

The causative agent of Lyme disease (LD), Borreliella burgdorferi, binds factor H (FH) and other complement regulatory proteins to its surface. B. burgdorferi B31 (type strain) encodes five FH-binding proteins (FHBPs): CspZ, CspA, and the OspE paralogs OspEBBN38, OspEBBL39, and OspEBBP38. This study assessed potential correlations between the production of individual FHBPs, FH-binding ability, and serum resistance using a panel of infectious B. burgdorferi clonal populations recovered from dogs. FHBP production was assessed in cultivated spirochetes and by antibody responses in naturally infected humans, dogs, and eastern coyotes (wild canids). FH binding specificity and sensitivity to dog and human serum were also assessed and compared. No correlation was observed between the production of individual FHBPs and FH binding with serum resistance, and CspA was determined to not be produced in animals. Notably, one or more clones isolated from dogs lacked CspZ or the OspE proteins (a finding confirmed by genome sequence determination) and did not bind FH derived from canines. The data presented do not support a correlation between FH binding and the production of individual FHBPs with serum resistance and infectivity. In addition, the limited number and polymorphic nature of cp32s in B. burgdorferi clone DRI85A that were identified through genome sequencing suggest no strict requirement for a defined set of these replicons for infectivity. This study reveals that the immune evasion mechanisms employed by B. burgdorferi are diverse, complex, and yet to be fully defined.

Riboformer: a deep learning framework for predicting context-dependent translation dynamics

Translation elongation is essential for maintaining cellular proteostasis, and alterations in the translational landscape are associated with a range of diseases. Ribosome profiling allows detailed measurements of translation at the genome scale. However, it remains unclear how to disentangle biological variations from technical artifacts in these data and identify sequence determinants of translation dysregulation. Here we present Riboformer, a deep learning-based framework for modeling context-dependent changes in translation dynamics. Riboformer leverages the transformer architecture to accurately predict ribosome densities at codon resolution. When trained on an unbiased dataset, Riboformer corrects experimental artifacts in previously unseen datasets, which reveals subtle differences in synonymous codon translation and uncovers a bottleneck in translation elongation. Further, we show that Riboformer can be combined with in silico mutagenesis to identify sequence motifs that contribute to ribosome stalling across various biological contexts, including aging and viral infection. Our tool offers a context-aware and interpretable approach for standardizing ribosome profiling datasets and elucidating the regulatory basis of translation kinetics.