Mesophiles vs. Thermophiles: Untangling the Hot Mess of Intrinsically Disordered Proteins and Growth Temperature of Bacteria.

The dynamic structures and varying functions of intrinsically disordered proteins (IDPs) have made them fascinating subjects in molecular biology. Investigating IDP abundance in different bacterial species is crucial for understanding adaptive strategies in diverse environments. Notably, thermophilic bacteria have lower IDP abundance than mesophiles, and a negative correlation with optimal growth temperature (OGT) has been observed. However, the factors driving these trends are yet to be fully understood. We examined the types of IDPs present in both mesophiles and thermophiles alongside those unique to just mesophiles. The shared group of IDPs exhibits similar disorder levels in the two groups of species, suggesting that certain IDPs unique to mesophiles may contribute to the observed decrease in IDP abundance as OGT increases. Subsequently, we used quasi-independent contrasts to explore the relationship between OGT and IDP abundance evolution. Interestingly, we found no significant relationship between OGT and IDP abundance contrasts, suggesting that the evolution of lower IDP abundance in thermophiles may not be solely linked to OGT. This study provides a foundation for future research into the intricate relationship between IDP evolution and environmental adaptation. Our findings support further research on the adaptive significance of intrinsic disorder in bacterial species.

Computational Design of Novel Griseofulvin Derivatives Demonstrating Potential Antibacterial Activity: Insights from Molecular Docking and Molecular Dynamics Simulation.

In response to the urgent demand for innovative antibiotics, theoretical investigations have been employed to design novel analogs. Because griseofulvin is a potential antibacterial agent, we have designed novel derivatives of griseofulvin to enhance its antibacterial efficacy and to evaluate their interactions with bacterial targets using in silico analysis. The results of this study reveal that the newly designed derivatives displayed the most robust binding affinities towards PBP2, tyrosine phosphatase, and FtsZ proteins. Additionally, molecular dynamics (MD) simulations underscored the notable stability of these derivatives when engaged with the FtsZ protein, as evidenced by root mean square deviation (RMSD), root mean square fluctuation (RMSF), radius of gyration (Rg), and solvent-accessible surface area (SASA). Importantly, this observation aligns with expectations, considering that griseofulvin primarily targets microtubules in eukaryotic cells, and FtsZ functions as the prokaryotic counterpart to microtubules. These findings collectively suggest the promising potential of griseofulvin and its designed derivatives as effective antibacterial agents, particularly concerning their interaction with the FtsZ protein. This research contributes to the ongoing exploration of novel antibiotics and may serve as a foundation for future drug development efforts.

In Silico Exploration of Microtubule Agent Griseofulvin and Its Derivatives Interactions with Different Human ß-Tubulin Isotypes.

Tubulin isotypes are known to regulate microtubule stability and dynamics, as well as to play a role in the development of resistance to microtubule-targeted cancer drugs. Griseofulvin is known to disrupt cell microtubule dynamics and cause cell death in cancer cells through binding to tubulin protein at the taxol site. However, the detailed binding mode involved molecular interactions, and binding affinities with different human ß-tubulin isotypes are not well understood. Here, the binding affinities of human ß-tubulin isotypes with griseofulvin and its derivatives were investigated using molecular docking, molecular dynamics simulation, and binding energy calculations. Multiple sequence analysis shows that the amino acid sequences are different in the griseofulvin binding pocket of ßI isotypes. However, no differences were observed at the griseofulvin binding pocket of other ß-tubulin isotypes. Our molecular docking results show the favorable interaction and significant affinity of griseofulvin and its derivatives toward human ß-tubulin isotypes. Further, molecular dynamics simulation results show the structural stability of most ß-tubulin isotypes upon binding to the G1 derivative. Taxol is an effective drug in breast cancer, but resistance to it is known. Modern anticancer treatments use a combination of multiple drugs to alleviate the problem of cancer cells resistance to chemotherapy. Our study provides a significant understanding of the involved molecular interactions of griseofulvin and its derivatives with ß-tubulin isotypes, which may help to design potent griseofulvin analogues for specific tubulin isotypes in multidrug-resistance cancer cells in future.

In Silico Molecular Dynamics of Griseofulvin and Its Derivatives Revealed Potential Therapeutic Applications for COVID-19.

Treatment options for Coronavirus Disease 2019 (COVID-19) remain limited, and the option of repurposing approved drugs with promising medicinal properties is of increasing interest in therapeutic approaches to COVID-19. Using computational approaches, we examined griseofulvin and its derivatives against four key anti-SARS-CoV-2 targets: main protease, RdRp, spike protein receptor-binding domain (RBD), and human host angiotensin-converting enzyme 2 (ACE2). Molecular docking analysis revealed that griseofulvin (CID 441140) has the highest docking score (-6.8 kcal/mol) with main protease of SARS-CoV-2. Moreover, griseofulvin derivative M9 (CID 144564153) proved the most potent inhibitor with -9.49 kcal/mol, followed by A3 (CID 46844082) with -8.44 kcal/mol against M protease and ACE2, respectively. Additionally, H bond analysis revealed that compound A3 formed the highest number of hydrogen bonds, indicating the strongest inhibitory efficacy against ACE2. Further, molecular dynamics (MD) simulation analysis revealed that griseofulvin and these derivatives are structurally stable. These findings suggest that griseofulvin and its derivatives may be considered when designing future therapeutic options for SARS-CoV-2 infection.

Quantitative Trait Locus Mapping of Marsh Spot Disease Resistance in Cranberry Common Bean (Phaseolus vulgaris L.).

Common bean (Phaseolus vulgaris L.) is a food crop that is an important source of dietary proteins and carbohydrates. Marsh spot is a physiological disorder that diminishes seed quality in beans. Prior research suggested that this disease is likely caused by manganese (Mn) deficiency during seed development and that marsh spot resistance is controlled by at least four genes. In this study, genetic mapping was performed to identify quantitative trait loci (QTL) and the potential candidate genes associated with marsh spot resistance. All 138 recombinant inbred lines (RILs) from a bi-parental population were evaluated for marsh spot resistance during five years from 2015 to 2019 in sandy and heavy clay soils in Morden, Manitoba, Canada. The RILs were sequenced using a genotyping by sequencing approach. A total of 52,676 single nucleotide polymorphisms (SNPs) were identified and filtered to generate a high-quality set of 2066 SNPs for QTL mapping. A genetic map based on 1273 SNP markers distributed on 11 chromosomes and covering 1599 cm was constructed. A total of 12 stable and 4 environment-specific QTL were identified using additive effect models, and an additional two epistatic QTL interacting with two of the 16 QTL were identified using an epistasis model. Genome-wide scans of the candidate genes identified 13 metal transport-related candidate genes co-locating within six QTL regions. In particular, two QTL (QTL.3.1 and QTL.3.2) with the highest R2 values (21.8% and 24.5%, respectively) harbored several metal transport genes Phvul.003G086300, Phvul.003G092500, Phvul.003G104900, Phvul.003G099700, and Phvul.003G108900 in a large genomic region of 16.8-27.5 Mb on chromosome 3. These results advance the current understanding of the genetic mechanisms of marsh spot resistance in cranberry common bean and provide new genomic resources for use in genomics-assisted breeding and for candidate gene isolation and functional characterization.

Griseofulvin: An Updated Overview of Old and Current Knowledge.

Griseofulvin is an antifungal polyketide metabolite produced mainly by ascomycetes. Since it was commercially introduced in 1959, griseofulvin has been used in treating dermatophyte infections. This fungistatic has gained increasing interest for multifunctional applications in the last decades due to its potential to disrupt mitosis and cell division in human cancer cells and arrest hepatitis C virus replication. In addition to these inhibitory effects, we and others found griseofulvin may enhance ACE2 function, contribute to vascular vasodilation, and improve capillary blood flow. Furthermore, molecular docking analysis revealed that griseofulvin and its derivatives have good binding potential with SARS-CoV-2 main protease, RNA-dependent RNA polymerase (RdRp), and spike protein receptor-binding domain (RBD), suggesting its inhibitory effects on SARS-CoV-2 entry and viral replication. These findings imply the repurposing potentials of the FDA-approved drug griseofulvin in designing and developing novel therapeutic interventions. In this review, we have summarized the available information from its discovery to recent progress in this growing field. Additionally, explored is the possible mechanism leading to rare hepatitis induced by griseofulvin. We found that griseofulvin and its metabolites, including 6-desmethylgriseofulvin (6-DMG) and 4- desmethylgriseofulvin (4-DMG), have favorable interactions with cytokeratin intermediate filament proteins (K8 and K18), ranging from -3.34 to -5.61 kcal mol-1. Therefore, they could be responsible for liver injury and Mallory body (MB) formation in hepatocytes of human, mouse, and rat treated with griseofulvin. Moreover, the stronger binding of griseofulvin to K18 in rodents than in human may explain the observed difference in the severity of hepatitis between rodents and human.

Effect of prophylactic use of hydrolyzed protein formula on gastrointestinal diseases and physical growth in preterm infants: a Meta analysis. / é¢„é˜²æ€§ä½¿ç”¨æ°´è§£è›‹ç™½é æ–¹å¥¶å¯¹æ—©äº§å„¿èƒƒè‚ é“ç–¾ç— åŠä½“æ ¼ç”Ÿé•¿å½±å“çš„Meta分析.

OBJECTIVES: To systematically evaluate the effect of prophylactic use of hydrolyzed protein formula on gastrointestinal diseases and physical development in preterm infants. METHODS: A computerized search was performed in the databases including China National Knowledge Infrastructure, Wanfang Data, Weipu, PubMed, Embase, and the Cochrane Library to identify randomized controlled trials of the effect of prophylactic use of hydrolyzed protein formula on gastrointestinal diseases and physical growth in preterm infants. RevMan 5.3 software was used to perform a Meta analysis for the included studies. RESULTS: A total of 7 randomized controlled studies were included. The results of Meta analysis showed that compared with the whole protein formula, the prophylactic use of hydrolyzed protein formula could reduce the risk of neonatal necrotizing enterocolitis (RR=0.40, P=0.04) and feeding intolerance (RR=0.40, P=0.005), and had no significant effect on the growth of weight, length and head circumference (P>0.05). CONCLUSIONS: Compared with the whole protein formula, the prophylactic use of hydrolyzed protein formula in preterm infants may reduce the occurrence of necrotizing enterocolitis and feeding intolerance, and can meet the nutrient requirement of physical development. However, the evidence is limited, and the results of this study cannot support the routine prophylactic use of hydrolyzed protein formula in preterm infants.

Applications of Protein Secondary Structure Algorithms in SARS-CoV-2 Research.

Since the outset of COVID-19, the pandemic has prompted immediate global efforts to sequence SARS-CoV-2, and over 450 000 complete genomes have been publicly deposited over the course of 12 months. Despite this, comparative nucleotide and amino acid sequence analyses often fall short in answering key questions in vaccine design. For example, the binding affinity between different ACE2 receptors and SARS-COV-2 spike protein cannot be fully explained by amino acid similarity at ACE2 contact sites because protein structure similarities are not fully reflected by amino acid sequence similarities. To comprehensively compare protein homology, secondary structure (SS) analysis is required. While protein structure is slow and difficult to obtain, SS predictions can be made rapidly, and a well-predicted SS structure may serve as a viable proxy to gain biological insight. Here we review algorithms and information used in predicting protein SS to highlight its potential application in pandemics research. We also showed examples of how SS predictions can be used to compare ACE2 proteins and to evaluate the zoonotic origins of viruses. As computational tools are much faster than wet-lab experiments, these applications can be important for research especially in times when quickly obtained biological insights can help in speeding up response to pandemics.

Extreme Genomic CpG Deficiency in SARS-CoV-2 and Evasion of Host Antiviral Defense.

Wild mammalian species, including bats, constitute the natural reservoir of betacoronavirus (including SARS, MERS, and the deadly SARS-CoV-2). Different hosts or host tissues provide different cellular environments, especially different antiviral and RNA modification activities that can alter RNA modification signatures observed in the viral RNA genome. The zinc finger antiviral protein (ZAP) binds specifically to CpG dinucleotides and recruits other proteins to degrade a variety of viral RNA genomes. Many mammalian RNA viruses have evolved CpG deficiency. Increasing CpG dinucleotides in these low-CpG viral genomes in the presence of ZAP consistently leads to decreased viral replication and virulence. Because ZAP exhibits tissue-specific expression, viruses infecting different tissues are expected to have different CpG signatures, suggesting a means to identify viral tissue-switching events. The author shows that SARS-CoV-2 has the most extreme CpG deficiency in all known betacoronavirus genomes. This suggests that SARS-CoV-2 may have evolved in a new host (or new host tissue) with high ZAP expression. A survey of CpG deficiency in viral genomes identified a virulent canine coronavirus (alphacoronavirus) as possessing the most extreme CpG deficiency, comparable with that observed in SARS-CoV-2. This suggests that the canine tissue infected by the canine coronavirus may provide a cellular environment strongly selecting against CpG. Thus, viral surveys focused on decreasing CpG in viral RNA genomes may provide important clues about the selective environments and viral defenses in the original hosts.

RNA-Seq approach for accurate characterization of splicing efficiency of yeast introns.

Introns in different genes, or even different introns within the same gene, often have different splice sites and differ in splicing efficiency (SE). One expects mass-transcribed genes to have introns with higher SE than weakly transcribed genes. However, such a simple expectation cannot be tested directly because variable SE for these genes is often not measured. Mechanistically, SE should depend on signal strength at key splice sites (SS) such as 5'SS, 3'SS and branchpoint site (BPS), i.e., SE = F(5'SS, 3'SS, BPS). However, without SE, we again cannot model how these splice sites contribute to SE. Here I present an RNA-Seq approach to quantify SE for each of the 304 introns in yeast (Saccharomyces cerevisiae) genes, including 24 in the 5'UTR, by measuring 1) number of reads mapped to exon-exon junctions (NEE) as a proxy for the abundance of spliced form, and 2) number of reads mapped to exon-intron junction (NEI5 and NEI3 at 5' and 3' ends of intron) as a proxy for the abundance of unspliced form. The total mRNA is NTotal = NEE + p * NEI5 + (1-p) * NEI3, with the simplest p = 0.5 but statistical methods were presented to estimate p from data. An estimated p is needed because NEI5 is expected to be smaller than NEI3 due to 1) step 1 splicing occurs before step 2 so EI5 is broken before EI3, 2) enrichment of poly(A) mRNA by oligo-dT, and 3) 5' degradation. SE is defined as the proportion (NEE/NTotal). Application of the method shows that ribosomal protein messages are efficiently and mostly cotranscriptionally spliced. Yeast genes with long introns are also spliced efficiently. HAC1/YFL031W is poorly spliced partly because its splicing involves a nonspliceosome mechanism and partly because Ire1p, which participate in splicing HAC1, is hardly expressed. Many putative yeast genes have low SE, and some splice sites are incorrectly annotated.

Drug efficacy and toxicity prediction: an innovative application of transcriptomic data.

Drug toxicity and efficacy are difficult to predict partly because they are both poorly defined, which I aim to remedy here from a transcriptomic perspective. There are two major categories of drugs: (1) restorative drugs aiming to restore an abnormal cell, tissue, or organ to normal function (e.g., restoring normal membrane function of epithelial cells in cystic fibrosis), and (2) disruptive drugs aiming to kill pathogens or malignant cells. These two types of drugs require different definition of efficacy and toxicity. I outlined rationales for defining transcriptomic efficacy and toxicity and illustrated numerically their application with two sets of transcriptomic data, one for restorative drugs (treating cystic fibrosis with lumacaftor/ivacaftor aiming to restore the cellular function of epithelial cells) and the other for disruptive drugs (treating acute myeloid leukemia with prexasertib). The conceptual framework presented will help and sensitize researchers to collect data required for determining drug toxicity.

[Efficacy and safety of fluconazole in prophylaxis of invasive fungal infections in very low birth weight infants: a Meta analysis].

OBJECTIVE: To assess the efficacy and safety of fluconazole in the prophylaxis of invasive fungal infection in very low birth weight (VLBW) infants. METHODS: Databases including PubMed, Embase, the Cochrane Library, Wanfang Data, Weipu, and CNKI were searched for randomized controlled trials (RCTs) of prophylactic fluconazole in VLBW infants. Review Manager 5.3 software was used to perform a Meta analysis of the included studies. RESULTS: A total of 12 RCTs were included, involving 1 679 VLBW infants. The Meta analysis showed that prophylactic fluconazole significantly reduced the incidence of invasive fungal infection (RR=0.44, 95%CI: 0.27-0.71, P<0.001), the incidence of fungal colonization (RR=0.31, 95%CI: 0.24-0.40, P<0.001), and the mortality during hospitalization (RR=0.74, 95%CI: 0.58-0.94, P=0.01) compared with the control group. There were no significant differences between VLBW infants using different doses of fluconazole in the incidence of invasive fungal infection and fungal colonization (P>0.05). No significant differences were found in the incidence of fluconazole resistance and complications between the fluconazole and control groups (P>0.05). CONCLUSIONS: Prophylactic fluconazole can effectively and safely prevent invasive fungal infection in VLBW infants, even at a small dose.

DAMBE7: New and Improved Tools for Data Analysis in Molecular Biology and Evolution.

DAMBE is a comprehensive software package for genomic and phylogenetic data analysis on Windows, Linux, and Macintosh computers. New functions include imputing missing distances and phylogeny simultaneously (paving the way to build large phage and transposon trees), new bootstrapping/jackknifing methods for PhyPA (phylogenetics from pairwise alignments), and an improved function for fast and accurate estimation of the shape parameter of the gamma distribution for fitting rate heterogeneity over sites. Previous method corrects multiple hits for each site independently. DAMBE's new method uses all sites simultaneously for correction. DAMBE, featuring a user-friendly graphic interface, is freely available from http://dambe.bio.uottawa.ca (last accessed, April 17, 2018).

Translation Control of HAC1 by Regulation of Splicing in Saccharomyces cerevisiae.

Hac1p is a key transcription factor regulating the unfolded protein response (UPR) induced by abnormal accumulation of unfolded/misfolded proteins in the endoplasmic reticulum (ER) in Saccharomyces cerevisiae. The accumulation of unfolded/misfolded proteins is sensed by protein Ire1p, which then undergoes trans-autophosphorylation and oligomerization into discrete foci on the ER membrane. HAC1 pre-mRNA, which is exported to the cytoplasm but is blocked from translation by its intron sequence looping back to its 5'UTR to form base-pair interaction, is transported to the Ire1p foci to be spliced, guided by a cis-acting bipartite element at its 3'UTR (3'BE). Spliced HAC1 mRNA can be efficiently translated. The resulting Hac1p enters the nucleus and activates, together with coactivators, a large number of genes encoding proteins such as protein chaperones to restore and maintain ER homeostasis and secretary protein quality control. This review details the translation regulation of Hac1p production, mediated by the nonconventional splicing, in the broad context of translation control and summarizes the evolution and diversification of the UPR signaling pathway among fungal, metazoan and plant lineages.

Coevolution between Stop Codon Usage and Release Factors in Bacterial Species.

Three stop codons in bacteria represent different translation termination signals, and their usage is expected to depend on their differences in translation termination efficiency, mutation bias, and relative abundance of release factors (RF1 decoding UAA and UAG, and RF2 decoding UAA and UGA). In 14 bacterial species (covering Proteobacteria, Firmicutes, Cyanobacteria, Actinobacteria and Spirochetes) with cellular RF1 and RF2 quantified, UAA is consistently over-represented in highly expressed genes (HEGs) relative to lowly expressed genes (LEGs), whereas UGA usage is the opposite even in species where RF2 is far more abundant than RF1. UGA usage relative to UAG increases significantly with PRF2 [=RF2/(RF1 + RF2)] as expected from adaptation between stop codons and their decoders. PRF2 is > 0.5 over a wide range of AT content (measured by PAT3 as the proportion of AT at third codon sites), but decreases rapidly toward zero at the high range of PAT3 This explains why bacterial lineages with high PAT3 often have UGA reassigned because of low RF2. There is no indication that UAG is a minor stop codon in bacteria as claimed in a recent publication. The claim is invalid because of the failure to apply the two key criteria in identifying a minor codon: (1) it is least preferred by HEGs (or most preferred by LEGs) and (2) it corresponds to the least abundant decoder. Our results suggest a more plausible explanation for why UAA usage increases, and UGA usage decreases, with PAT3, but UAG usage remains low over the entire PAT3 range.

DAMBE6: New Tools for Microbial Genomics, Phylogenetics, and Molecular Evolution.

DAMBE is a comprehensive software workbench for data analysis in molecular biology, phylogenetics, and evolution. Several important new functions have been added since version 5 of DAMBE: 1) comprehensive genomic profiling of translation initiation efficiency of different genes in different prokaryotic species, 2) a new index of translation elongation (ITE) that takes into account both tRNA-mediated selection and background mutation on codon-anticodon adaptation, 3) a new and accurate phylogenetic approach based on pairwise alignment only, which is useful for highly divergent sequences from which a reliable multiple sequence alignment is difficult to obtain. Many other functions have been updated and improved including PWM for motif characterization, Gibbs sampler for de novo motif discovery, hidden Markov models for protein secondary structure prediction, self-organizing map for nonlinear clustering of transcriptomic data, comprehensive sequence alignment, and phylogenetic functions. DAMBE features a graphic, user-friendly and intuitive interface, and is freely available from http://dambe.bio.uottawa.ca.

PhyPA: Phylogenetic method with pairwise sequence alignment outperforms likelihood methods in phylogenetics involving highly diverged sequences.

While pairwise sequence alignment (PSA) by dynamic programming is guaranteed to generate one of the optimal alignments, multiple sequence alignment (MSA) of highly divergent sequences often results in poorly aligned sequences, plaguing all subsequent phylogenetic analysis. One way to avoid this problem is to use only PSA to reconstruct phylogenetic trees, which can only be done with distance-based methods. I compared the accuracy of this new computational approach (named PhyPA for phylogenetics by pairwise alignment) against the maximum likelihood method using MSA (the ML+MSA approach), based on nucleotide, amino acid and codon sequences simulated with different topologies and tree lengths. I present a surprising discovery that the fast PhyPA method consistently outperforms the slow ML+MSA approach for highly diverged sequences even when all optimization options were turned on for the ML+MSA approach. Only when sequences are not highly diverged (i.e., when a reliable MSA can be obtained) does the ML+MSA approach outperforms PhyPA. The true topologies are always recovered by ML with the true alignment from the simulation. However, with MSA derived from alignment programs such as MAFFT or MUSCLE, the recovered topology consistently has higher likelihood than that for the true topology. Thus, the failure to recover the true topology by the ML+MSA is not because of insufficient search of tree space, but by the distortion of phylogenetic signal by MSA methods. I have implemented in DAMBE PhyPA and two approaches making use of multi-gene data sets to derive phylogenetic support for subtrees equivalent to resampling techniques such as bootstrapping and jackknifing.

Evolution of the highly networked deubiquitinating enzymes USP4, USP15, and USP11.

BACKGROUND: USP4, USP15 and USP11 are paralogous deubiquitinating enzymes as evidenced by structural organization and sequence similarity. Based on known interactions and substrates it would appear that they have partially redundant roles in pathways vital to cell proliferation, development and innate immunity, and elevated expression of all three has been reported in various human malignancies. The nature and order of duplication events that gave rise to these extant genes has not been determined, nor has their functional redundancy been established experimentally at the organismal level. METHODS: We have employed phylogenetic and syntenic reconstruction methods to determine the chronology of the duplication events that generated the three paralogs and have performed genetic crosses to evaluate redundancy in mice. RESULTS: Our analyses indicate that USP4 and USP15 arose from whole genome duplication prior to the emergence of jawed vertebrates. Despite having lower sequence identity USP11 was generated later in vertebrate evolution by small-scale duplication of the USP4-encoding region. While USP11 was subsequently lost in many vertebrate species, all available genomes retain a functional copy of either USP4 or USP15, and through genetic crosses of mice with inactivating mutations we have confirmed that viability is contingent on a functional copy of USP4 or USP15. Loss of ubiquitin-exchange regulation, constitutive skipping of the seventh exon and neural-specific expression patterns are derived states of USP11. Post-translational modification sites differ between USP4, USP15 and USP11 throughout evolution. CONCLUSIONS: In isolation sequence alignments can generate erroneous USP gene phylogenies. Through a combination of methodologies the gene duplication events that gave rise to USP4, USP15, and USP11 have been established. Although it operates in the same molecular pathways as the other USPs, the rapid divergence of the more recently generated USP11 enzyme precludes its functional interchangeability with USP4 and USP15. Given their multiplicity of substrates the emergence (and in some cases subsequent loss) of these USP paralogs would be expected to alter the dynamics of the networks in which they are embedded.

Differential codon adaptation between dsDNA and ssDNA phages in Escherichia coli.

Because phages use their host translation machinery, their codon usage should evolve toward that of highly expressed host genes. We used two indices to measure codon adaptation of phages to their host, rRSCU (the correlation in relative synonymous codon usage [RSCU] between phages and their host) and Codon Adaptation Index (CAI) computed with highly expressed host genes as the reference set (because phage translation depends on host translation machinery). These indices used for this purpose are appropriate only when hosts exhibit little mutation bias, so only phages parasitizing Escherichia coli were included in the analysis. For double-stranded DNA (dsDNA) phages, both r(RSCU) and CAI decrease with increasing number of transfer RNA genes encoded by the phage genome. r(RSCU) is greater for dsDNA phages than for single-stranded DNA (ssDNA) phages, and the low r(RSCU) values are mainly due to poor concordance in RSCU values for Y-ending codons between ssDNA phages and the E. coli host, consistent with the predicted effect of C→T mutation bias in the ssDNA phages. Strong C→T mutation bias would improve codon adaptation in codon families (e.g., Gly) where U-ending codons are favored over C-ending codons ("U-friendly" codon families) by highly expressed host genes but decrease codon adaptation in other codon families where highly expressed host genes favor C-ending codons against U-ending codons ("U-hostile" codon families). It is remarkable that ssDNA phages with increasing C→T mutation bias also increased the usage of codons in the "U-friendly" codon families, thereby achieving CAI values almost as large as those of dsDNA phages. This represents a new type of codon adaptation.