Recurring cluster and operon assembly for Phenylacetate degradation genes

Tracing the ancestry of operons in bacteria

MOTIVATION

Complexity is a fundamental attribute of life. Complex systems are made of parts that together perform functions that a single component, or subsets of components, cannot. Examples of complex molecular systems include protein structures such as the F1Fo-ATPase, the ribosome, or the flagellar motor: each one of these structures requires most or all of its components to function properly. Given the ubiquity of complex systems in the biosphere, understanding the evolution of complexity is central to biology. At the molecular level, operons are classic examples of a complex system. An operon's genes are co-transcribed under the control of a single promoter to a polycistronic mRNA molecule, and the operon's gene products often form molecular complexes or metabolic pathways. With the large number of complete bacterial genomes available, we now have the opportunity to explore the evolution of these complex entities, by identifying possible intermediate states of operons.

RESULTS

In this work, we developed a maximum parsimony algorithm to reconstruct ancestral operon states, and show a simple vertical evolution model of how operons may evolve from the individual component genes. We describe several ancestral states that are plausible functional intermediate forms leading to the full operon. We also offer Reconstruction of Ancestral Gene blocks Using Events or ROAGUE as a software tool for those interested in exploring gene block and operon evolution.

AVAILABILITY AND IMPLEMENTATION

The software accompanying this paper is available under GPLv3 license on: https://github.com/nguyenngochuy91/Ancestral-Blocks-Reconstruction.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

The evolutionary life cycle of the polysaccharide biosynthetic gene cluster based on the Sphingomonadaceae

Although clustering of genes from the same metabolic pathway is a widespread phenomenon, the evolution of the polysaccharide biosynthetic gene cluster remains poorly understood. To determine the evolution of this pathway, we identified a scattered production pathway of the polysaccharide sanxan by Sphingomonas sanxanigenens NX02, and compared the distribution of genes between sphingan-producing and other Sphingomonadaceae strains. This allowed us to determine how the scattered sanxan pathway developed, and how the polysaccharide gene cluster evolved. Our findings suggested that the evolution of microbial polysaccharide biosynthesis gene clusters is a lengthy cyclic process comprising cluster 1 → scatter → cluster 2. The sanxan biosynthetic pathway proved the existence of a dispersive process. We also report the complete genome sequence of NX02, in which we identified many unstable genetic elements and powerful secretion systems. Furthermore, nine enzymes for the formation of activated precursors, four glycosyltransferases, four acyltransferases, and four polymerization and export proteins were identified. These genes were scattered in the NX02 genome, and the positive regulator SpnA of sphingans synthesis could not regulate sanxan production. Finally, we concluded that the evolution of the sanxan pathway was independent. NX02 evolved naturally as a polysaccharide producing strain over a long-time evolution involving gene acquisitions and adaptive mutations.

Convergent evolution of the arginine deiminase pathway: the ArcD and ArcE arginine/ornithine exchangers

The arginine deiminase (ADI) pathway converts L-arginine into L-ornithine and yields 1 mol of ATP per mol of L-arginine consumed. The L-arginine/L-ornithine exchanger in the pathway takes up L-arginine and excretes L-ornithine from the cytoplasm. Analysis of the genomes of 1281 bacterial species revealed the presence of 124 arc gene clusters encoding the pathway. About half of the clusters contained the gene encoding the well-studied L-arginine/L-ornithine exchanger ArcD, while the other half contained a gene, termed here arcE, encoding a membrane protein that is not a homolog of ArcD. The arcE gene product of Streptococcus pneumoniae was shown to take up L-arginine and L-ornithine with affinities of 0.6 and 1 μmol/L, respectively, and to catalyze metabolic energy-independent, electroneutral exchange. ArcE of S. pneumoniae could replace ArcD in the ADI pathway of Lactococcus lactis and provided the cells with a growth advantage. In contrast to ArcD, ArcE catalyzed translocation of the pathway intermediate L-citrulline with high efficiency. A short version of the ADI pathway is proposed for L-citrulline catabolism and the presence of the evolutionary unrelated arcD and arcE genes in different organisms is discussed in the context of the evolution of the ADI pathway.

Horizontally transferred genes cluster spatially and metabolically

Background

Genomic uptake of DNA by prokaryotes often encompasses more than a single gene. In many cases, several horizontally transferred genes may be acquired together. Accordingly, we expect that horizontally transferred genes cluster spatially in the genome more often than expected if transfers were independent. Further, genes that depend on each other functionally may be unlikely to have beneficial fitness effects when taken up individually by a foreign genome. Hence, we also expect the co-acquisition of functionally related genes, resulting in the clustering of horizontally transferred genes in functional networks.

Results

Analysing spatial and metabolic clustering of recent horizontal (or lateral) gene transfers among 21 γ-proteobacteria, we confirm both predictions. When comparing two datasets of predicted transfers that differ in their expected false-positive rate, we find that the more stringent dataset shows a stronger enrichment of clustered pairs.

Conclusions

The enrichment of interdependent metabolic genes among predicted transfers supports a biologically significant role of horizontally transferred genes in metabolic adaptation. Our results further suggest that spatial and metabolic clustering may be used as a benchmark for methods that predict recent horizontal gene transfers.

Reviewers

This article was reviewed by Peter Gogarten in collaboration with Luiz Thiberio Rangel, and by Yuri Wolf.

The role of thionins in rice defence against root pathogens

Thionins are antimicrobial peptides that are involved in plant defence. Here, we present an in-depth analysis of the role of rice thionin genes in defence responses against two root pathogens: the root-knot nematode Meloidogyne graminicola and the oomycete Pythium graminicola. The expression of rice thionin genes was observed to be differentially regulated by defence-related hormones, whereas all analysed genes were consistently down-regulated in M. graminicola-induced galls, at least until 7 days post-inoculation (dpi). Transgenic lines of Oryza sativa cv. Nipponbare overproducing OsTHI7 revealed decreased susceptibility to M. graminicola infection and P. graminicola colonization. Taken together, these results demonstrate the role of rice thionin genes in defence against two of the most damaging root pathogens attacking rice.

An event-driven approach for studying gene block evolution in bacteria

Motivation: Gene blocks are genes co-located on the chromosome. In many cases, gene blocks are conserved between bacterial species, sometimes as operons, when genes are co-transcribed. The conservation is rarely absolute: gene loss, gain, duplication, block splitting and block fusion are frequently observed. An open question in bacterial molecular evolution is that of the formation and breakup of gene blocks, for which several models have been proposed. These models, however, are not generally applicable to all types of gene blocks, and consequently cannot be used to broadly compare and study gene block evolution. To address this problem, we introduce an event-based method for tracking gene block evolution in bacteria.

Results: We show here that the evolution of gene blocks in proteobacteria can be described by a small set of events. Those include the insertion of genes into, or the splitting of genes out of a gene block, gene loss, and gene duplication. We show how the event-based method of gene block evolution allows us to determine the evolutionary rateand may be used to trace the ancestral states of their formation. We conclude that the event-based method can be used to help us understand the formation of these important bacterial genomic structures.

Availability and implementation: The software is available under GPLv3 license on http://github.com/reamdc1/gene_block_evolution.git. Supplementary online material: http://iddo-friedberg.net/operon-evolution

Contact:i.friedberg@miamioh.edu

Supplementary information:Supplementary data are available at Bioinformatics online.

A systematic computational analysis of biosynthetic gene cluster evolution: lessons for engineering biosynthesis

Bacterial secondary metabolites are widely used as antibiotics, anticancer drugs, insecticides and food additives. Attempts to engineer their biosynthetic gene clusters (BGCs) to produce unnatural metabolites with improved properties are often frustrated by the unpredictability and complexity of the enzymes that synthesize these molecules, suggesting that genetic changes within BGCs are limited by specific constraints. Here, by performing a systematic computational analysis of BGC evolution, we derive evidence for three findings that shed light on the ways in which, despite these constraints, nature successfully invents new molecules: 1) BGCs for complex molecules often evolve through the successive merger of smaller sub-clusters, which function as independent evolutionary entities. 2) An important subset of polyketide synthases and nonribosomal peptide synthetases evolve by concerted evolution, which generates sets of sequence-homogenized domains that may hold promise for engineering efforts since they exhibit a high degree of functional interoperability, 3) Individual BGC families evolve in distinct ways, suggesting that design strategies should take into account family-specific functional constraints. These findings suggest novel strategies for using synthetic biology to rationally engineer biosynthetic pathways.

Bacterial secondary metabolites mediate a broad range of microbe-microbe and microbe-host interactions, and are widely used in human medicine, agriculture and manufacturing. Despite recent advances in synthetic biology, efforts to engineer their biosynthetic genes for the production of unnatural variants are frustrated by a high failure rate. In an effort to better understand what types of genetic changes are most likely to lead to successful improvements, we systematically analyzed the ways in which biosynthetic genes naturally evolve to generate new compounds. We show that large gene clusters appear to evolve through the merger of sub-clusters, which function independently, and are promising units for cluster engineering. Moreover, a subset of gene clusters evolve by concerted evolution, which generates sets of interoperable domains that may enable predictable domain swapping. Finally, many biosynthetic gene clusters evolve in family-specific modes that differ greatly from each other. Overall, this quantitative perspective on the ways in which gene clusters naturally evolve suggests novel strategies for using synthetic biology to engineer the production of unnatural metabolites.

Goods-thinking vs. tree-thinking: Finding a place for mobile genetic elements

While it has become increasingly clear that the Tree of Life hypothesis has limitations in its ability to describe the evolution of all evolving entities on the planet, there has been a marked reluctance to move away from the tree-based language. Ironically, while modifying the idea of the Tree of Life to the extent that it is only very distantly related to its original descriptions, there has been a very careful attempt to retain the language of tree-thinking. The recent movement away from a tree-thinking language toward a goods-thinking language and perspective is a significant improvement. In this commentary, we describe how goods-thinking can provide better descriptions of evolution, can integrate evolution with environment more closely and can offer an equal place for Mobile Genetic Elements and chromosomal elements in discussions of evolutionary history.

Insights on the regulation of the phenylacetate degradation pathway from Escherichia coli

The paa genes for phenylacetic acid (PA) catabolism encode the best characterized aerobic hybrid route involved in the bacterial degradation of aromatic compounds. Here, we demonstrate that the divergent paaZ and paaA-K catabolic operons of Escherichia coli are regulated by two genes, paaXY, that form a distinct transcriptional unit driven by the Px promoter. In vivo and in vitro approaches using purified PaaX regulatory protein revealed that this regulator is able to bind and inhibit the activity of Px in a phenylacetyl-coenzyme A (PA-CoA) dependent manner. The autoregulation of paaXY is due to the competition between PaaX and RNA polymerase for binding to the regulatory Px promoter. Whereas a similar mechanism of repression mediated by PaaX was shown to occur at the catabolic Pz promoter; the catabolic Pa promoter is inhibited by PaaX by a mechanism that does not involves competition with RNA polymerase. We have shown for the first time that the paaY gene product is essential for an efficient growth in PA. Purified PaaY was shown to be a trimer in solution with a broad thioesterase activity stimulated by some metals. This thioesterase activity will allow the detoxification of some CoA-intermediates that block the aerobic catabolism of PA, as previously suggested, but also will avoid the accumulation of some CoA derivatives that could behave as antagonists of the inducer effect caused by PA-CoA on the PaaX repressor for an efficient expression of the paa genes. This regulatory function mediated by PaaY constitutes an additional regulatory checkpoint that makes the circuit that controls the transcription of the paa genes more complex than previously thought, and it could represent a general strategy present in most bacterial paa gene clusters that also harbour the paaY gene.

Alignment-free distance measure based on return time distribution for sequence analysis: applications to clustering, molecular phylogeny and subtyping

The data deluge in post-genomic era demands development of novel data mining tools. Existing molecular phylogeny analyses (MPAs) developed for individual gene/protein sequences are alignment-based. However, the size of genomic data and uncertainties associated with alignments, necessitate development of alignment-free methods for MPA. Derivation of distances between sequences is an important step in both, alignment-dependant and alignment-free methods. Various alignment-free distance measures based on oligo-nucleotide frequencies, information content, compression techniques, etc. have been proposed. However, these distance measures do not account for relative order of components viz. nucleotides or amino acids. A new distance measure, based on the concept of 'return time distribution' (RTD) of k-mers is proposed, which accounts for the sequence composition and their relative orders. Statistical parameters of RTDs are used to derive a distance function. The resultant distance matrix is used for clustering and phylogeny using Neighbor-joining. Its performance for MPA and subtyping was evaluated using simulated data generated by block-bootstrap, receiver operating characteristics and leave-one-out cross validation methods. The proposed method was successfully applied for MPA of family Flaviviridae and subtyping of Dengue viruses. It is observed that method retains resolution for classification and subtyping of viruses at varying levels of sequence similarity and taxonomic hierarchy.

Phenylacetic acid catabolism and its transcriptional regulation in Corynebacterium glutamicum

The industrially important organism Corynebacterium glutamicum has been characterized in recent years for its robust ability to assimilate aromatic compounds. In this study, C. glutamicum strain AS 1.542 was investigated for its ability to catabolize phenylacetic acid (PAA). The paa genes were identified; they are organized as a continuous paa gene cluster. The type strain of C. glutamicum, ATCC 13032, is not able to catabolize PAA, but the recombinant strain ATCC 13032/pEC-K18mob2::paa gained the ability to grow on PAA. The paaR gene, encoding a TetR family transcription regulator, was studied in detail. Disruption of paaR in strain AS 1.542 resulted in transcriptional increases of all paa genes. Transcription start sites and putative promoter regions were determined. An imperfect palindromic motif (5'-ACTNACCGNNCGNNCGGTNAGT-3'; 22 bp) was identified in the upstream regions of paa genes. Electrophoretic mobility shift assays (EMSA) demonstrated specific binding of PaaR to this motif, and phenylacetyl coenzyme A (PA-CoA) blocked binding. It was concluded that PaaR is the negative regulator of PAA degradation and that PA-CoA is the PaaR effector. In addition, GlxR binding sites were found, and binding to GlxR was confirmed. Therefore, PAA catabolism in C. glutamicum is regulated by the pathway-specific repressor PaaR, and also likely by the global transcription regulator GlxR. By comparative genomic analysis, we reconstructed orthologous PaaR regulons in 57 species, including species of Actinobacteria, Proteobacteria, and Flavobacteria, that carry PAA utilization genes and operate by conserved binding motifs, suggesting that PaaR-like regulation might commonly exist in these bacteria.

Regulation of phenylacetic acid uptake is σ54 dependent in Pseudomonas putida CA-3

Background

Styrene is a toxic and potentially carcinogenic alkenylbenzene used extensively in the polymer processing industry. Significant quantities of contaminated liquid waste are generated annually as a consequence. However, styrene is not a true xenobiotic and microbial pathways for its aerobic assimilation, via an intermediate, phenylacetic acid, have been identified in a diverse range of environmental isolates. The potential for microbial bioremediation of styrene waste has received considerable research attention over the last number of years. As a result the structure, organisation and encoded function of the genes responsible for styrene and phenylacetic acid sensing, uptake and catabolism have been elucidated. However, a limited understanding persists in relation to host specific regulatory molecules which may impart additional control over these pathways. In this study the styrene degrader Pseudomonas putida CA-3 was subjected to random mini-Tn5 mutagenesis and mutants screened for altered styrene/phenylacetic acid utilisation profiles potentially linked to non-catabolon encoded regulatory influences.

Results

One mutant, D7, capable of growth on styrene, but not on phenylacetic acid, harboured a Tn5 insertion in the rpoN gene encoding σ54. Complementation of the D7 mutant with the wild type rpoN gene restored the ability of this strain to utilise phenylacetic acid as a sole carbon source. Subsequent RT-PCR analyses revealed that a phenylacetate permease, PaaL, was expressed in wild type P. putida CA-3 cells utilising styrene or phenylacetic acid, but could not be detected in the disrupted D7 mutant. Expression of plasmid borne paaL in mutant D7 was found to fully restore the phenylacetic acid utilisation capacity of the strain to wild type levels. Bioinformatic analysis of the paaL promoter from P. putida CA-3 revealed two σ⁵⁴ consensus binding sites in a non-archetypal configuration, with the transcriptional start site being resolved by primer extension analysis. Comparative analyses of genomes encoding phenylacetyl CoA, (PACoA), catabolic operons identified a common association among styrene degradation linked PACoA catabolons in Pseudomonas species studied to date.

Conclusions

In summary, this is the first study to report RpoN dependent transcriptional activation of the PACoA catabolon paaL gene, encoding a transport protein essential for phenylacetic acid utilisation in P. putida CA-3. Bioinformatic analysis is provided to suggest this regulatory link may be common among styrene degrading Pseudomonads.

Genomic clustering of cyanogenic glucoside biosynthetic genes aids their identification in Lotus japonicus and suggests the repeated evolution of this chemical defence pathway

Cyanogenic glucosides are amino acid-derived defence compounds found in a large number of vascular plants. Their hydrolysis by specific β-glucosidases following tissue damage results in the release of hydrogen cyanide. The cyanogenesis deficient1 (cyd1) mutant of Lotus japonicus carries a partial deletion of the CYP79D3 gene, which encodes a cytochrome P450 enzyme that is responsible for the first step in cyanogenic glucoside biosynthesis. The genomic region surrounding CYP79D3 contains genes encoding the CYP736A2 protein and the UDP-glycosyltransferase UGT85K3. In combination with CYP79D3, these genes encode the enzymes that constitute the entire pathway for cyanogenic glucoside biosynthesis. The biosynthetic genes for cyanogenic glucoside biosynthesis are also co-localized in cassava (Manihot esculenta) and sorghum (Sorghum bicolor), but the three gene clusters show no other similarities. Although the individual enzymes encoded by the biosynthetic genes in these three plant species are related, they are not necessarily orthologous. The independent evolution of cyanogenic glucoside biosynthesis in several higher plant lineages by the repeated recruitment of members from similar gene families, such as the CYP79s, is a likely scenario.

PR-1 gene family of grapevine: a uniquely duplicated PR-1 gene from a Vitis interspecific hybrid confers high level resistance to bacterial disease in transgenic tobacco

A functional contribution of pathogenesis-related 1 (PR-1) proteins to host defense has been established. However, systematic investigation of the PR-1 gene family in grapevine (Vitis spp.) has not been conducted previously. Through mining genomic databases, we identified 21 PR-1 genes from the Vitis vinifera genome. Polypeptides encoded by putative PR-1 genes had a signal sequence of about 25 residues and a mature protein of 10.9-29 kDa in size. PR-1 mature proteins contained a highly conserved six-cysteine motif and pI values ranging from 4.6 to 9. A major cluster with 14 PR-1 genes was mapped to a 280-kb region on chromosome 3. One particular PR-1 gene within the cluster encoding a basic-type isoform (pI 7.77), herein named VvPR1b1, was isolated from various genotypes of grapevine (Vitis spp.) for functional studies. Sequence analysis of PCR-amplified DNA revealed that all genotypes contained a single VvPR1b1 gene except for a broad-spectrum bacterial and fungal disease resistant Florida bunch grape hybrid, 'BN5-4', from which seven different homologues were identified. Duplication of VvPR1b1-related genes encoding acidic-type PR-1 isoforms was also observed among several genotypes. However, transgenic expression analysis of grapevine PR-1 genes under strong constitutive promoters in transgenic tobacco revealed that only the basic-type VvPR1b1 gene duplicated in 'BN5-4' was capable of conferring high level resistance to bacterial disease caused by Pseudomonas syringae pv. tabaci.

Evolutionary origins of metabolic compartmentalization in eukaryotes

Many genes in eukaryotes are acquisitions from the free-living antecedents of chloroplasts and mitochondria. But there is no evolutionary 'homing device' that automatically directs the protein product of a transferred gene back to the organelle of its provenance. Instead, the products of genes acquired from endosymbionts can explore all targeting possibilities within the cell. They often replace pre-existing host genes, or even whole pathways. But the transfer of an enzymatic pathway from one compartment to another poses severe problems: over evolutionary time, the enzymes of the pathway acquire their targeting signals for the new compartment individually, not in unison. Until the whole pathway is established in the new compartment, newly routed individual enzymes are useless, and their genes will be lost through mutation. Here it is suggested that pathways attain novel compartmentation variants via a 'minor mistargeting' mechanism. If protein targeting in eukaryotic cells possesses enough imperfection such that small amounts of entire pathways continuously enter novel compartments, selectable units of biochemical function would exist in new compartments, and the genes could become selected. Dual-targeting of proteins is indeed very common within eukaryotic cells, suggesting that targeting variation required for this minor mistargeting mechanism to operate exists in nature.

Conditions for the evolution of gene clusters in bacterial genomes

Genes encoding proteins in a common pathway are often found near each other along bacterial chromosomes. Several explanations have been proposed to account for the evolution of these structures. For instance, natural selection may directly favour gene clusters through a variety of mechanisms, such as increased efficiency of coregulation. An alternative and controversial hypothesis is the selfish operon model, which asserts that clustered arrangements of genes are more easily transferred to other species, thus improving the prospects for survival of the cluster. According to another hypothesis (the persistence model), genes that are in close proximity are less likely to be disrupted by deletions. Here we develop computational models to study the conditions under which gene clusters can evolve and persist. First, we examine the selfish operon model by re-implementing the simulation and running it under a wide range of conditions. Second, we introduce and study a Moran process in which there is natural selection for gene clustering and rearrangement occurs by genome inversion events. Finally, we develop and study a model that includes selection and inversion, which tracks the occurrence and fixation of rearrangements. Surprisingly, gene clusters fail to evolve under a wide range of conditions. Factors that promote the evolution of gene clusters include a low number of genes in the pathway, a high population size, and in the case of the selfish operon model, a high horizontal transfer rate. The computational analysis here has shown that the evolution of gene clusters can occur under both direct and indirect selection as long as certain conditions hold. Under these conditions the selfish operon model is still viable as an explanation for the evolution of gene clusters.

Genes involved in a common pathway or function are frequently found near each other on bacterial chromosomes. A number of hypotheses have been previously presented to explain this observation. A particularly influential theory is the selfish operon model, which posits that horizontal transfer could promote gene clustering by favouring transfer of arrangements of genes that are close together. Subsequent theoretical development and analysis of genomic data have contributed to the debate about the plausibility of this model. Here, by re-examining the evolutionary dynamics of gene clusters, we provide and discuss conditions under which gene clusters can evolve. We find that first, some form of bias for clustering is required for clusters to evolve. This bias can be in the form of bias in horizontal transfer towards genes that are close together, or direct natural selection for gene proximity. Our computational work does not present a theoretical obstacle to the selfish operon model as a possible explanation for the evolution of gene clusters.

Identification and characterization of a NADH oxidoreductase involved in phenylacetic acid degradation pathway from Streptomyces peucetius

Annotation of genome of Streptomyces peucetius revealed a putative phenylacetic acid degradation NADH oxidoreductase. RT-PCR analysis of the gene readily showed notable transcription in its native state. The transcription level of paaE when the host is grown on phenylacetic acid showed increased transcription. paaE was cloned into a pET32a(+) vector to overexpress the protein coupled with fusion tags in Escherichia coli BL21(DE3) and purified by immobilized metal affinity chromatography using His-tag. The flavin released from heat-denatured PaaE was identical to that of authentic FAD in HPLC analysis. The purified protein efficiently reduced p-nitroblue tetrazolium (an electron acceptor) in presence of NADH. Cell growth analysis of S. peucetius in phenylacetic acid evidently revealed its involvement in degradation of phenylacetic acid - a key environmental pollutant.

Stochasticity in protein levels drives colinearity of gene order in metabolic operons of Escherichia coli

Gene order in some bacterial metabolic operons reflects ordering in the metabolic pathway. That this is true uniquely for operons expressed at low levels highlights the selective importance of fluctuations in protein levels.

In bacterial genomes, gene order is not random. This is most evident when looking at operons, these often encoding enzymes involved in the same metabolic pathway or proteins from the same complex. Is gene order within operons nonrandom, however, and if so why? We examine this issue using metabolic operons as a case study. Using the metabolic network of Escherichia coli, we define the temporal order of reactions. We find a pronounced trend for genes to appear in operons in the same order as they are needed in metabolism (colinearity). This is paradoxical as, at steady state, enzymes abundance should be independent of order within the operon. We consider three extensions of the steady-state model that could potentially account for colinearity: (1) increased productivity associated with higher expression levels of the most 5′ genes, (2) a faster metabolic processing immediately after up-regulation, and (3) metabolic stalling owing to stochastic protein loss. We establish the validity of these hypotheses by employing deterministic and stochastic models of enzyme kinetics. The stochastic stalling hypothesis correctly and uniquely predicts that colinearity is more pronounced both for lowly expressed operons and for genes that are not physically adjacent. The alternative models fail to find any support. These results support the view that stochasticity is a pervasive problem to a cell and that gene order evolution can be driven by the selective consequences of fluctuations in protein levels.

In bacteria, different enzymes from the same metabolic pathway are often encoded within one transcriptional unit, an operon. There is also, we show, a tendency for the enzymes that are needed earlier in the pathway to feature earlier in the operon, so-called colinearity. Why might this be? We test three ideas, one old and two new. The prior suggestion supposes that proteins of genes early in operons will be at a higher dose. Although some operons are like this, in general, we see no relationship of protein dose with colinearity. We also find no evidence that operons that frequently need up-regulation are any more likely to be colinear. A third model is, however, supported. If an operon is rarely expressed, then all the proteins for this part of metabolism can be lost by chance. Rebooting such metabolism is fastest if the operon is colinear. This model predicts, correctly, that colinearity should be more frequent in operons that are expressed at a low level. This result is important for at least two reasons. First, it supports the view that chance events (such as protein loss) within cells are important on a day-to-day basis. Second, it challenges the supposition that natural selection will be weakest on lowly expressed genes. Where chance events are concerned, natural selection can be strong on genes expressed at a low level.