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PubMed1994

Potential secondary structure at the translational start domain of eukaryotic and prokaryotic mRNAs.

In order to identify conserved potential secondary structures within translational start sites, mRNA sequences derived from different species were studied with programs able to depict such features. The potential secondary structure of 71 bases around the initiator AUG or AUGs in the coding sequences of 290 eukaryotic mRNAs was first examined and compared to 290 similarly analyzed regions derived from prokaryotic mRNA sequences (Nucleic Acids Res (1987) 15, 345-360). In both sets of sequences the initiator codon was often found to be in an open potential structure whereas a denser region characterized by nearly-periodic spacings defined the coding regions. Randomization of the sequences obliterated the observed patterns suggesting that the structure of the mRNA may determine these differences. Three sets of eukaryotic and prokaryotic mRNAs of approximately equal length were analyzed and found to preserve an open unpaired non-coding region 5' to the start codon. The start codon was found free of potential secondary structure in over 80% of all the sequences analyzed. These data, and study of mutants that restrict the accessibility of the start codon to the ribosomal initiation complex, suggest that both the prokaryotic and eukaryotic mRNA start sites must occur free of potential secondary structure for efficient initiation. A striking difference of the eukaryotic mRNA sequences analyzed was the high propensity of the coding region vicinal to the start codon to form secondary structures. Certain translation-defective mutants exhibit impaired formation of these secondary structures suggesting that the structure of the coding regions adjacent to the start codons of eukaryotic mRNAs may be an important, thus far unexamined, determinant of initiation. We propose that, for all genes studied, the transition in secondary structure between the coding and non-coding regions may be an important determinant of initiation.

Animals↗
PubMed1995

An interactive framework for RNA secondary structure prediction with a dynamical treatment of constraints.

A novel approach aiding in the prediction of RNA secondary structures is presented. Although phylogenetic methods are the most successful at deriving RNA secondary structures, the are not applicable when the number of sequences or the sequence variability is too low. Methods based on energy minimization are therefore of great interest. However, some of the suboptimal RNA secondary structures computed with classic methods are unsaturated structures, i.e. some structures are included into others. Thus, the incorporation of constraints during the process of folding is not possible, while the incorporation of constraints before the process of folding often introduces a bias into the energy function. This paper describes a new procedure which allows for the incorporation of constraints before and during the process of RNA folding. SAPSSARN is an interactive program which offers a framework, both to specify a secondary structure through a set of folding constraints and to compute all the supoptimal saturated RNA secondary structures which satisfy all the folding constraints. At the start, it relies on the computation of the probabilities of pairing of each base with all others according to McCaskill's algorithm. The constraint satisfaction formulation of the problem deals dynamically with a chosen set of folding constraints and, finally, a search algorithm computes all the suboptimal saturated secondary structures which satisfy those folding constraints. Within such a framework, it is possible to test new ideas about RNA folding and secondary structures, including pseudoknots, can be computed. The program is illustrated with RNA sequences on which we obtained results in agreement with known structures by using a protocol which mimics the hierarchical folding of RNA molecules.

Algorithms↗
PubMed1999

Identification of beta-turn and random coil amide III infrared bands for secondary structure estimation of proteins.

Fourier transform infrared spectroscopy is increasingly becoming an important method to determine secondary structure of peptides and proteins. Among the spectral regions arising out of coupled and uncoupled stretching and bending modes of amide bonds, amide I and amide III spectral bands have been found to be the most sensitive to the variations in secondary structure folding. Amide I spectral region (1700-1600 cm-1), although most commonly used primarily because of its strong signal, suffers from several limitations, including a strong interference from water vibrational band, relatively unstructured spectral contour, and overlap of revolved bands correspondingly to various secondary structures. In contrast, amide III spectral region (1350-1200 cm-1), albeit relatively weak in signals, does not have the above limitations. Easily resolved and better defined amide III bands are quite suitable for quantitative analysis of protein secondary structure. While amide III region has been successfully used for determination of alpha-helix and beta-sheets (Fu, F.-N., et al. (1994) Appl. Spectrosc. 48, 1432-1441), bands corresponding to beta-turns and random coils have not been identified, so far. In this paper, we describe, for the first time, identification of amide III bands corresponding to beta-turns and random coils by selectively enhancing random coils by treatment with a denaturing reagent, and secondary structure estimation of several proteins by using the band assignments. The assignments of spectral bands were as follows: 1330-1295 cm-1, alpha-helix; 1295-1270 cm-1, beta-turns; 1270-1250 cm-1, random coils; and 1250-1220 cm-1, beta-sheets. The estimations of secondary structural elements by the above assignments correlated quite well with secondary structure estimations from X-ray crystallography data.

Amides↗
PubMedDate not supplied

Use of variable selection in modeling the secondary structural content of proteins from their composition of amino acid residues.

The possibility of prediction of protein secondary structure content from composition of their amino acid residues can help in bridging the gap between proteins of known primary sequence having an unknown secondary structure. Almost all recently published models for understanding the relationship between composition (frequency of occurrence) of amino acid residues and secondary structure content of proteins involved composition of all 20 amino acid residues. However, it is well-known that many amino acid residues are mutually similar according to their physicochemical properties (hydrophobicity, hydrophilicity, charge, size, etc.). Because of that, we were motivated to investigate the possibility of reduction of the total number of terms (frequencies of amino acid residues) in the models for describing the relation between the composition of amino acid residues and the percentage of residues belonging to alpha, beta, and coil secondary structure. For this purpose, the CROMRsel algorithm (J. Chem. Inf. Comput. Sci. 1999, 39, 121-132) for selection of a small subset of the most important variables/descriptors into the multiregression (MR) models, i.e., frequency of occurrence of amino acid residues in proteins, was used. Analysis was performed on a data set containing 475 proteins, taken from Proteins 1996, 25, 157-168. A complete data set was partitioned into a 317-protein training set and 158-protein test set. The best possible linear models containing I=1, ..., 20 frequencies were selected among all 20 frequencies of occurrence of amino acid residues on the 317-protein training set, and were used for performing prediction of the corresponding percentage of secondary structure content on the 158-protein test set. For the 317-protein data set the best selected concise models for the alpha, beta, and coil secondary structure contain only 9, 5, and 8 frequencies, respectively. Selected concise models are of the same or better fitted, cross-validated, and predictive statistical parameters than the models containing all 20 frequencies. Additionally, for each I (I=1, ...., 20) 30 the best possible random models were selected. In each case, the best possible real models are much better than each of the best possible random models, showing clearly that there is no risk of a chance correlation (what one could expect due to the application of an exhaustive search for the best model having I frequencies among all 20!/I!(20-I)! possible models). Finally, the best selected models on the complete 475-protein data set for the alpha, beta, and coil secondary structure contain only 7, 4, and 7 frequencies of amino acid residues, respectively. These models are much simpler and have better fitted and cross-validated errors than the corresponding models from the literature, that were obtained without using a procedure for selection of the most important frequencies of amino acid residues in proteins.

Amino Acids↗
PubMed1990

Secondary structure of the human membrane-associated folate binding protein using a joint prediction approach.

The secondary structures of the human membrane-associated folate binding protein (FBP) and bovine soluble FBP are assessed by a joint prediction approach that combines neural network models, information theory, homology modeling and the Chou-Fasman methods. Two new profile maps are used to characterize the non-regular secondary structure and to assist in assigning buried and exposed parts of secondary structure: (i) the loop potential profile and (ii) the long range contact profile. Approximately half of human FBP is predicted to form regular secondary structure (alpha-helices-35% or beta-sheets - 12%, excluding the transmembrane helices) and the rest is predicted to form coil, turns or loops. The bovine milk soluble FBP is predicted to have a similar secondary structure as expected because of the high degree of homology between the FBP's. Discriminant analysis predicts two transmembrane segments for the human FBP sequence, one at the amino terminus (a leader sequence) and the other at the carboxy terminus. These predicted transmembrane domains are absent in the bovine milk soluble FBP, further supporting these predictions. The present set of secondary structural predictions for human FBP is obtained by 'consensus' to aid in modeling the super-secondary structure of the protein.

Amino Acid Sequence↗
PubMed1993

Secondary structural features of modules M2 and M3 of barnase in solution by NMR experiment and distance geometry calculation.

Proteins consist of structural units such as globular domains, secondary structures, and modules. Modules were originally defined by partitioning a globular domain into compact regions, each of which is a contiguous polypeptide segment having a compact conformation. Since modules show close correlations with the intron positions of genes, they are regarded as primordial polypeptide pieces encoded by exons and shuffled, leading to yield new combination of them in early biological evolution. Do modules maintain their native conformations in solution when they are excised at their boundaries? In order to find answers to this question, we have synthesized modules of barnase, one of the bacterial RNases, and studied the solution structures of modules M2 (amino acid residues 24-52) and M3 (52-73) by 2D NMR studies. Some local secondary structures, alpha-helix, and beta-turns in M2 and beta-turns in M3, were observed in the modules at the similar positions to those in the intact barnase but the overall state seems to be in a mixture of random and native conformations. The present result shows that the excised modules have propensity to form similar secondary structures to those of the intact barnase.

Amino Acid Sequence↗
PubMed1987

Comparisons of large subunit rRNAs reveal some eukaryote-specific elements of secondary structure.

All large rRNAs possess a common core of secondary structure. However, large variations in the size of the molecule have arisen during evolution, which are accommodated over a dozen rapidly evolving domains. Most of the enlargement of the eukaryotic molecules (as compared to prokaryotes) is in fact restricted over only two of these divergent domains, which are dramatically expanded in vertebrates. We have derived secondary structure models for these two domains through a systematic comparison of all the pro- and eukaryotic sequences published so far. Within each of these domains, a subset of secondary structure elements which are specific to eukaryotes is detected. Archaebacterial-specific secondary structures can also be identified which appear to be maintained through a strong selective constraint. The relative preservation of such group-specific structures raises the issue of their potential involvement in some diversification of ribosomal functions among the three fundamental phylogenetic groups, eubacteria, archaebacteria and eukaryotes. We also show that eukaryotic ribosomal RNAs are subjected, over their entire length, to a unique type of compositional constraint which may largely differ among the major eukaryotic taxa.

Animals↗
PubMed1994

The origins of protein secondary structure. Effects of packing density and hydrogen bonding studied by a fast conformational search.

Globular proteins fold to create compact structures rich in alpha-helices and beta-sheets. While studies of cubic lattice models of simplified polypeptide chains have concluded that secondary structure is a necessary consequence of chain compactness, different conclusions have been reached from studies of off-lattice models of simplified chains. In an attempt to resolve this controversy, we study an all-atom off-lattice model of a protein subject to a variety of simplified energy functions. A Monte Carlo simulated annealing algorithm is used to search conformational space quickly. The algorithm uses pivot-type moves in which a residue is selected at random and the values of its main-chain dihedral angles are changed. The energy function used to accept or reject moves is taken to be either a term proportional to the volume occupied by a structure (to mimic the hydrophobic effect), a term proportional to the energy of main-chain hydrogen bonding, or a combination of these two terms. Secondary structure content is evaluated using several different definitions. For all the definitions used, compactness alone produces a 10% increase in secondary structure content. However, this is a small fraction of the secondary structure observed in native protein structures. Structures produced by minimizing the hydrogen bond energy have extensive secondary structure but are not densely packed. Structures having both the high density of native structures and extensive secondary structure are produced by minimizing combinations of the volume and hydrogen bond energy terms. Our results emphasize the close relationship between secondary structure and the geometry of main-chain hydrogen bonding. The results are consistent with a description of protein folding in which the hydrophobic effect favors dense packing while hydrogen bonding determines the specific local geometry which generates secondary structure. To make an analogy with lattice studies of packing density and secondary structure, it seems that hydrophobicity provides the packing density while hydrogen bonding provides the lattice.

Algorithms↗
PubMed1984

Comparative study on the secondary structure of lysozymes from different sources.

The secondary structure of 16 type c lysozymes, 2 type g lysozymes, phage T4 lysozyme and bovine alpha-lactalbumin have been estimated according to the method of Chou and Fasman (1978). The prediction has been done on the partial sequence of lysozymes from three insects and tortoise egg-white lysozyme. From these studies, patterns of common secondary structure domains on lysozymes have been developed. These patterns have been compared attending to the active site and the antigenic loop of the hen enzyme of which three-dimensional structure is known. The three-dimensional structures of phage T4 and hen egg-white lysozymes have common alpha-carbon backbone domains being that also observed by these predictions. Immunological results are also discussed in terms of secondary structure homologies.

Amino Acids↗
PubMed1994

Structural features can be unconserved in proteins with similar folds. An analysis of side-chain to side-chain contacts secondary structure and accessibility.

Side-chain to side-chain contacts, accessibility, secondary structure and RMS deviation were compared within 607 pairs of proteins having similar three-dimensional (3D) structures. Three types of protein 3D structural similarities were defined: type A having sequence and usually functional similarity; type B having functional, but no sequence similarity; and type C having only 3D structural similarity. Within proteins having little or no sequence similarity (types B and C), structural features frequently had a degree of conservation comparable to dissimilar 3D structures. Despite similar protein folds, as few as 30% of residues within similar protein 3D structures can form a common core. RMS deviations on core C alpha atoms can be as high as 3.2 A. Similar protein structures can have secondary structure identities as low as 41%, which is equivalent to that expected by chance. By defining three categories of amino acid accessibility (buried, half buried and exposed), some similar protein 3D structures have as few as 30% of positions in the same category, making them indistinguishable from pairs of dissimilar protein structures. Similar structures can also have as few as 12% of common side-chain to side-chain contacts, and virtually no similar energetically favourable side-chain to side-chain interactions. Complementary changes are defined as structurally equivalent pairs of interacting residues in two structures with energetically favourable but different side-chain interactions. For many proteins with similar three-dimensional structures, the proportion of complementary changes is near to that expected by chance, suggesting that many similar structures have fundamentally different stabilising interactions. All of the results suggest that proteins having similar 3D structures can have little in common apart from a scaffold of core secondary structures. This has profound implications for methods of protein fold detection, since many of the properties assumed to be conserved across similar protein 3D structures (e.g. accessibility, side-chain to side-chain contacts, etc.) are often unconserved within weakly similar (i.e. type B and C) protein 3D structures. Little difference was found between type B and C similarities suggesting that the structure of similar proteins can evolve beyond recognition even when function is conserved. Our findings suggest that it is more general features of protein structure, such as the requirements for burial of hydrophobic residues and exposure of polar residues, rather than specific residue-residue interactions that determine how well a particular sequence adopts a particular fold.(ABSTRACT TRUNCATED AT 400 WORDS)

Amino Acid Sequence↗
PubMed1996

Identifying the tertiary fold of small proteins with different topologies from sequence and secondary structure using the genetic algorithm and extended criteria specific for strand regions.

Grid-free protein folding simulations based on sequence and secondary structure knowledge (using mostly experimentally determined secondary structure information but also analysing results from secondary structure predictions) were investigated using the genetic algorithm, a backbone representation, and standard dihedral angular conformations. Optimal structures are selected according to basic protein building principles. Having previously applied this approach to proteins with helical topology, we have now developed additional criteria and weights for beta-strand-containing proteins, validated them on four small beta-strand-rich proteins with different topologies, and tested the general performance of the method on many further examples from known protein structures with mixed secondary structural type and less than 100 amino acid residues. Topology predictions close to the observed experimental structures were obtained in four test cases together with fitness values that correlated with the similarity of the predicted topology to the observed structures. Root-mean-square deviation values of C alpha atoms in the superposed predicted and observed structures, the latter of which had different topologies, were between 4.5 and 5.5 A(2.9 to 5.1 A without loops). Including 15 further protein examples with unique folds, root-mean-square deviation values ranged between 1.8 and 6.9 A with loop regions and averaged 5.3 A and 4.3 A, including and excluding loop regions, respectively.

Algorithms↗
PubMed2002

Continuum secondary structure captures protein flexibility.

The DSSP program assigns protein secondary structure to one of eight states. This discrete assignment cannot describe the continuum of thermal fluctuations. Hence, a continuous assignment is proposed. Technically, the continuum results from averaging over ten discrete DSSP assignments with different hydrogen bond thresholds. The final continuous assignment for a single NMR model successfully reflected the structural variations observed between all NMR models in the ensemble. The structural variations between NMR models were verified to correlate with thermal motion; these variations were captured by the continuous assignments. Because the continuous assignment reproduces the structural variation between many NMR models from one single model, functionally important variation can be extracted from a single X-ray structure. Thus, continuous assignments of secondary structure may affect future protein structure analysis, comparison, and prediction.

Computer Systems↗
PubMed2004

Foldability, enzymatic activity, and interacting ability of barnase mutants obtained by permutation of secondary structure units.

Barnase, a well-characterized ribonuclease, has been decomposed into six modules (M1-M6) or secondary structure units (S1-S6). We have studied the foldability and activity of the barnase mutants obtained by permutation of the four internal modules (M2-M5) or secondary structure units (S2-S5) to investigate whether permutation of these building blocks is a useful way to create foldable and/or functional proteins. In this study, we found that one of the secondary structure unit mutants was expressed in Escherichia coli only when His102 was substituted by alanine, which is a catalytic residue of wild-type barnase. This mutant (S2354H102A) had ordered conformations, which unfolded cooperatively during urea-induced unfolding experiments. S2354H102A interacted with other barnase mutants to show a distinct RNase activity, although its own activity was quite weak. This interaction was specific, because S2354H102A interacted with only barnase mutants having His 102 and certain orders of the secondary structure units giving a distinct RNase activity. These results suggest that secondary structure units permuted in barnase mutants maintain their intrinsic "interacting ability" that is used for the folding of wild-type barnase, and the units can form certain conformations that complement those of the appropriate counterparts. Seven of 23 secondary structure unit mutants and only 2 of 23 module mutants had RNase activity. On the basis of the results of analyses of foldability and RNase activity of the mutants performed in this and previous studies, we conclude that secondary structure units are more suitable than modules as building blocks to create novel foldable and/or functional proteins in the case of barnase.

Alanine↗
PubMed1996

A comparative CD study of carbonic anhydrase isoenzymes with different number of tryptophans: impact on calculation of secondary structure content.

The CD spectra of human carbonic anhydrase I and II and bovine carbonic anhydrase III were recorded and analyzed. The 3D structures of these isoenzymes are known, showing very similar secondary structure and polypeptide-chain fold. The tryptophan content, however, differs between the isoenzymes, i.e., isoenzymes I, II, and III possess 6, 7, and 8 tryptophans, respectively. All of the tryptophans except the additional tryptophans in isoenzymes II and III, i.e., W245 and W47, are conserved. Despite the fact that X-ray structure determinations showed that the isoenzymes had highly similar secondary structure, the contents of alpha-helix and beta-sheet structure differed considerably when using different CD algorithms for estimation of the fractions of various secondary structural elements. This shows that aromatic amino acids also interfere in the wavelength region (far-UV) used to calculate the amount of secondary structure. Such interference is especially problematic when analyzing proteins like carbonic anhydrase, which consist mainly of beta-structure that gives rise to weak ellipticity bands, compared to the bands arising from alpha-helical structure.

Animals↗
PubMed2006

Improved alignment quality by combining evolutionary information, predicted secondary structure and self-organizing maps.

BACKGROUND: Protein sequence alignment is one of the basic tools in bioinformatics. Correct alignments are required for a range of tasks including the derivation of phylogenetic trees and protein structure prediction. Numerous studies have shown that the incorporation of predicted secondary structure information into alignment algorithms improves their performance. Secondary structure predictors have to be trained on a set of somewhat arbitrarily defined states (e.g. helix, strand, coil), and it has been shown that the choice of these states has some effect on alignment quality. However, it is not unlikely that prediction of other structural features also could provide an improvement. In this study we use an unsupervised clustering method, the self-organizing map, to assign sequence profile windows to "structural states" and assess their use in sequence alignment. RESULTS: The addition of self-organizing map locations as inputs to a profile-profile scoring function improves the alignment quality of distantly related proteins slightly. The improvement is slightly smaller than that gained from the inclusion of predicted secondary structure. However, the information seems to be complementary as the two prediction schemes can be combined to improve the alignment quality by a further small but significant amount. CONCLUSION: It has been observed in many studies that predicted secondary structure significantly improves the alignments. Here we have shown that the addition of self-organizing map locations can further improve the alignments as the self-organizing map locations seem to contain some information that is not captured by the predicted secondary structure.

Computational Biology↗
PubMed2005

Multicomponent peak modeling of protein secondary structures: comparison of gaussian with lorentzian analytical methods for plant feed and seed molecular biology and chemistry research.

The objective of this study was to compare Gaussian and Lorentzian multicomponent peak modeling methods in quantification of protein secondary structures of various plant seed and feed tissues within intact tissue at a cellular and subcellular level using the advanced synchrotron light sourced Fourier transform infrared (FT-IR) microspectroscopy (S-FTIR). This experiment was performed at the beamline U10B at the National Synchrotron Light Source (NSLS) in Brookhaven National Laboratory (BNL), U.S. Dept of Energy (NSLS-BNL, NY). The results show that in the comparison of the Gaussian and Lorentzian multi-peak modeling methods, the Gaussian method is more accurate for fitting multi-peak curves of protein secondary structures than the Lorentzian method, with higher modeling R(2) values (0.92 versus 0.89, P < 0.05). There were no large differences (P > 0.05) in the quantification of the relative percentage alpha-helices, beta-sheets, and others in protein secondary structures of the plant seed tissues, with averages of 30.2%, 40.4%, and 29.4%, respectively. However, there are significant differences (P < 0.05) in the quantification of the ratios of sheet alpha-helix (1.42 versus 1.60; SEM = 0.058) in protein secondary structures of the plant seed tissues. With synchrotron FT-IR microspectroscopy, the ultrastructural-chemical makeup and nutritive characteristics could be revealed at a high spatial resolution. Synchrotron-based FT-IR microspectroscopy revealed that the secondary structure of protein differed between the plant seed tissues in terms of relative percentage and ratio of protein secondary structures (alpha-helix and beta-sheet) within cellular dimensions. The results also show that the flaxseed tissues contained higher (P < 0.05) percentage alpha-helix (38.6 versus 24.0%) beta-sheet (45.3 versus 36.9%), lower (P < 0.05) percentage of other secondary structures (16.1% versus 39.0%), and higher (P < 0.05) ratios alpha-helix beta-sheet (0.90 versus 0.69) than the winterfat seed tissues. It must be mentioned that the relative percentages of protein secondary structure may not reflect the true secondary structure. However, the purpose of modeling the relative percentage of secondary structure was to detect the variety of differences among seed/feed/plant tissues and their relation to nutritive value and digestive behavior. The results demonstrate the potential of highly spatially resolved synchrotron-based FT-IR microspectroscopy to reveal protein secondary structures of the plant seed/feed tissues. Further study is needed to quantify the relationship between protein secondary structures and nutrient availability and digestive behavior of various varieties of plant seed tissues. Information from the infrared probing of protein secondary structures can be valuable as a guide to maintaining protein nutritive value and quality for animal and human use.

Algorithms↗
PubMed1998

JPred: a consensus secondary structure prediction server.

UNLABELLED: An interactive protein secondary structure prediction Internet server is presented. The server allows a single sequence or multiple alignment to be submitted, and returns predictions from six secondary structure prediction algorithms that exploit evolutionary information from multiple sequences. A consensus prediction is also returned which improves the average Q3 accuracy of prediction by 1% to 72.9%. The server simplifies the use of current prediction algorithms and allows conservation patterns important to structure and function to be identified. AVAILABILITY: http://barton.ebi.ac.uk/servers/jpred.h tml CONTACT: geoff@ebi.ac.uk

Algorithms↗
PubMed1980

Electron microscopic mapping of secondary structures in bacterial 16S and 23S ribosomal ribonucleic acid and 30S precursor ribosomal ribonucleic acid.

Electron microscopy revealed reproducible secondary structure patterns within partially denatured 16S and 23S ribosomal ribonucleic acid (rRNA) from Escherichia coli. When prepared with 50% formamide-100 mM ammonium acetate, 16S rRNA included two small hairpins that appeared in over 50% of all molecules. Three open loops were observed with frequencies of less than 25%. In contrast, 23S rRNA included a terminal open loop and two additional large structures in over 75% of all molecules. These secondary structure patterns were conserved in the 16S and 23S rRNA from Pseudomonas aeruginosa. The secondary structure of the 30S precursor rRNA from the ribonclease III-deficient E. coli mutant AB105 was mapped after partial denaturation in 70% formamide-100 mM ammonium acetate. Two large open loops were superimposed on the 16S and 23S rRNA secondary structure patterns. These loops were the most frequent structures found on the precursor, and their stems coincided with ribonuclease III cleavage sites. A tentative 5'-3 orientation was determined for the secondary structure patterns of 16S and 23S rRNA from their relative locations within 30S precursor rRNA. The relation of secondary structure to ribosomal protein binding and ribonuclease III cleavage is discussed.

Escherichia coli↗