Comparison of 432 Pseudomonas strains through integration of genomic, functional, metabolic and expression data

Koehorst, Jasper J.; Dam, Jesse C. J. van; Heck, Ruben G. A. van; Saccenti, Edoardo; Santos, Vítor A. P. Martins dos; Suárez-Diez, María; Schaap, Peter J.

doi:10.1038/srep38699

Cited by 64 publications

(64 citation statements)

References 55 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The core-genome of a taxonomic group contains genes that are present in all members of that group whereas the pan-genome contains all the different genes that can be found in any member of the population 30 . Here we extended the idea to protein domain classes, as has been previously reported 21,31 . We observed that most domain classes have a low persistence overall ( Figure 5), but as shown in Figure 6, by adding taxonomic information, distinct sets of domain classes accumulate in the core domainomes of the various clades, suggesting that these core sets are somehow contributing to the physiology and ecology of these clades.…”

Section: /15mentioning

confidence: 91%

Expected and observed genotype complexity in prokaryotes: correlation between 16S-rRNA phylogeny and protein domain content

Koehorst

Schaap

Suárez-Diez

2018

Preprint

Self Cite

View full text Add to dashboard Cite

BackgroundThe omnipresent 16S ribosomal RNA gene (16S-rRNA) is commonly used to identify and classify bacteria though it does not take into account the distinctive functional characteristics of taxa. We explored functional domain landscapes of over 5700 complete bacterial genomes, representing a wide coverage of the bacterial tree of life, and investigated to what extent the observed protein domain diversity correlates with the expected evolutionary diversity, using 16S-rRNA as metric for evolutionary distance. Results Analysis of protein domains showed that 83% of the bacterial genes code for at least one of the 9722 domain classes identified. By comparing clade specific and global persistence scores, candidate horizontal gene transfer and signifying domains could be identified. 16S-rRNA and functional domain content distances were used to evaluate and compare species divergence and overall a sigmoid curve is observed. Already at close 16S-rRNA evolutionary distances, high levels of functional diversity can be observed. At a larger 16S-rRNA distance, functional differences accumulate at a relatively lower pace. Conclusions Analysis of 16S-rRNA sequences in the same taxa suggests that, in many cases, additional means of classification are required to obtain reliable phylogenetic relationships. Whole genome protein domain class phylogenies correlate with, and complement 16S-rRNA sequence-based phylogenies. Moreover, domain-based phylogenies can be constructed over large evolutionary distances and provide an in-depth insight of the functional diversity within and among species and enables large scale functional comparisons. The increased granularity obtained paves way for new applications to better predict the relationships between genotype, physiology and ecology. 2/15 4/15

show abstract

Section: /15mentioning

confidence: 91%

Expected and observed genotype complexity in prokaryotes: correlation between 16S-rRNA phylogeny and protein domain content

Koehorst

Schaap

Suárez-Diez

2018

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…The DehI in the (10), and Pseudomonas putida AJ1 (23). To avoid potential misannotations, the selected genomes were de novo reannotated using the SAPP framework (46,47). Genes were identified using Prodigal (2.6.3) (48), and protein annotation was performed though protein domains using InterProScan (5.19-58.0) (49).…”

Section: Methodsmentioning

confidence: 99%

Concurrent Haloalkanoate Degradation and Chlorate Reduction by Pseudomonas chloritidismutans AW-1^T

Peng

Koehorst

Schaap

et al. 2017

Appl Environ Microbiol

Self Cite

View full text Add to dashboard Cite

Haloalkanoates are environmental pollutants that can be degraded aerobically by microorganisms producing hydrolytic dehalogenases. However, there is a lack of information about the anaerobic degradation of haloalkanoates. Genome analysis of Pseudomonas chloritidismutans AW-1 T , a facultative anaerobic chloratereducing bacterium, showed the presence of two putative haloacid dehalogenase genes, the L-DEX gene and dehI, encoding an L-2-haloacid dehalogenase (L-DEX) and a halocarboxylic acid dehydrogenase (DehI), respectively. Hence, we studied the concurrent degradation of haloalkanoates and chlorate as a yet-unexplored trait of strain AW-1 T . The deduced amino acid sequences of L-DEX and DehI revealed 33 to 37% and 26 to 86% identities with biochemically/structurally characterized L-DEX and the D-and DL-2-haloacid dehalogenase enzymes, respectively. Physiological experiments confirmed that strain AW-1 T can grow on chloroacetate, bromoacetate, and both L-and D-␣-halogenated propionates with chlorate as an electron acceptor. Interestingly, growth and haloalkanoate degradation were generally faster with chlorate as an electron acceptor than with oxygen as an electron acceptor. In line with this, analyses of L-DEX and DehI dehalogenase activities using cell-free extract (CFE) of strain AW-1 T grown on DL-2-chloropropionate under chlorate-reducing conditions showed up to 3.5-fold higher dehalogenase activity than the CFE obtained from AW-1 T cells grown on DL-2-chloropropionate under aerobic conditions. Reverse transcriptionquantitative PCR showed that the L-DEX gene was expressed constitutively independently of the electron donor (haloalkanoates or acetate) or acceptor (chlorate or oxygen), whereas the expression of dehI was induced by haloalkanoates. Concurrent degradation of organic and inorganic halogenated compounds by strain AW-1 T represents a unique metabolic capacity in a single bacterium, providing a new piece of the puzzle of the microbial halogen cycle.IMPORTANCE Halogenated organic and inorganic compounds are important environmental pollutants that have carcinogenic and genotoxic effects on both animals and humans. Previous research studied the degradation of organic and inorganic halogenated compounds separately but not concurrently. This study shows concurrent degradation of halogenated alkanoates and chlorate as an electron donor and acceptor, respectively, coupled to growth in a single bacterium, Pseudomonas chloritidismutans AW-1 T . Hence, besides biogenesis of molecular oxygen from chlorate reduction enabling a distinctive placement of strain AW-1 T between aerobic and anaerobic microorganisms, we can now add another unique metabolic potential of this bacterium to the roster. The degradation of different halogenated compounds under anoxic conditions by a single bacterium is also of interest for the natural halogen cycle in different aquatic and terrestrial ecosystems where ample natural production of halogenated compounds has been documented.

show abstract

“…The genome was annotated using the SAPP annotation pipeline, (Koehorst et al, 2016a). For gene prediction Prodigal version 2.6.2 (Hyatt et al, 2010) with codon table 4 was used.…”

Section: Genome Annotationmentioning

confidence: 99%

Metabolic modeling of energy balances in Mycoplasma hyopneumoniae shows that pyruvate addition increases growth rate

Kamminga

Slagman

Bijlsma

et al. 2017

Biotech & Bioengineering

Self Cite

View full text Add to dashboard Cite

Mycoplasma hyopneumoniae is cultured on large‐scale to produce antigen for inactivated whole‐cell vaccines against respiratory disease in pigs. However, the fastidious nutrient requirements of this minimal bacterium and the low growth rate make it challenging to reach sufficient biomass yield for antigen production. In this study, we sequenced the genome of M. hyopneumoniae strain 11 and constructed a high quality constraint‐based genome‐scale metabolic model of 284 chemical reactions and 298 metabolites. We validated the model with time‐series data of duplicate fermentation cultures to aim for an integrated model describing the dynamic profiles measured in fermentations. The model predicted that 84% of cellular energy in a standard M. hyopneumoniae cultivation was used for non‐growth associated maintenance and only 16% of cellular energy was used for growth and growth associated maintenance. Following a cycle of model‐driven experimentation in dedicated fermentation experiments, we were able to increase the fraction of cellular energy used for growth through pyruvate addition to the medium. This increase in turn led to an increase in growth rate and a 2.3 times increase in the total biomass concentration reached after 3–4 days of fermentation, enhancing the productivity of the overall process. The model presented provides a solid basis to understand and further improve M. hyopneumoniae fermentation processes. Biotechnol. Bioeng. 2017;114: 2339–2347. © 2017 The Authors. Biotechnology and Bioengineering published by Wiley Periodicals, Inc.

show abstract

Comparison of 432 Pseudomonas strains through integration of genomic, functional, metabolic and expression data

Cited by 64 publications

References 55 publications

Expected and observed genotype complexity in prokaryotes: correlation between 16S-rRNA phylogeny and protein domain content

Expected and observed genotype complexity in prokaryotes: correlation between 16S-rRNA phylogeny and protein domain content

Concurrent Haloalkanoate Degradation and Chlorate Reduction by Pseudomonas chloritidismutans AW-1^T

Metabolic modeling of energy balances in Mycoplasma hyopneumoniae shows that pyruvate addition increases growth rate

Contact Info

Product

Resources

About

Comparison of 432 Pseudomonas strains through integration of genomic, functional, metabolic and expression data

Cited by 64 publications

References 55 publications

Expected and observed genotype complexity in prokaryotes: correlation between 16S-rRNA phylogeny and protein domain content

Expected and observed genotype complexity in prokaryotes: correlation between 16S-rRNA phylogeny and protein domain content

Concurrent Haloalkanoate Degradation and Chlorate Reduction by Pseudomonas chloritidismutans AW-1T

Metabolic modeling of energy balances in Mycoplasma hyopneumoniae shows that pyruvate addition increases growth rate

Contact Info

Product

Resources

About

Concurrent Haloalkanoate Degradation and Chlorate Reduction by Pseudomonas chloritidismutans AW-1^T