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Ng, W.

Publications and source records attributed to Ng, W..

4 recordsLinked to original sources
bioRxiv2020

Effect of polyethylene glycol on growth of Escherichia coli DH5α and Bacillus subtilis NRS-762

Polyethylene glycol is commonly used in fermentation as an anti-foam for preventing the rise of foam to the top plate of the bioreactor, which increases contamination risk. However, its potential toxicity to growth of various microorganisms is not well understood at the species and strain level. Hence, the objective of this study was to understand the impact of different concentrations of polyethylene glycol at the 1, 5 and 10 g/L level on the aerobic growth of Escherichia coli DH5 and Bacillus subtilis NRS-762 in LB Lennox medium in shake flasks. Experiment results revealed that polyethylene glycol (PEG) (molecular weight [~]8000 Da), at all concentrations tested, did not affect biomass formation and metabolism in E. coli DH5 at 37 {degrees}C. This came about through the observation of similar maximal optical density obtained during growth of E. coli DH5 under differing concentrations of PEG. Furthermore, the anti-foam did not affect the pH profile. On the other hand, PEG did exhibit some toxicity towards the growth of B. subtilis NRS-762 in LB Lennox medium. Specifically, maximal optical density obtained decline with higher exposure to PEG in a concentration dependent manner, up to a threshold concentration of 5 g/L. For example, maximal optical density obtained in B. subtilis NRS-762 without addition of PEG was 4.4, but the value obtained with 1 g/L of the anti-foam decreased to 4.1 and a further 3.8 on exposure to 5 g/L and 10 g/L PEG. pH variation in culture broth, however, told a different story, where the profiles for exposure to PEG at all concentrations coincide with each other and was similar to the one without exposure to the anti-foam; thereby, suggesting that metabolic processes in B. subtilis NRS-762 were not significantly affected by exposure to PEG. Collectively, PEG anti-foam exerted species-specific toxicity effect on biomass formation, and possibly metabolism. The latter may not be sufficiently significant to affect the types of metabolites secreted by the bacterium, and thus, be detected by measurement of pH of culture broth. E. coli DH5 was better able to cope with PEG at all concentrations compared to B. subtilis NRS-762, which showed dose-dependent toxicity effect on biomass formation. HighlightsO_LIPolyethylene glycol (molecular weight [~] 8000 Da) did not affect aerobic growth of Escherichia coli DH5 at 37 {degrees}C in LB medium at all concentrations tested: 0, 1, 5, 10 g/L. C_LIO_LIGrowth curves of the bacterium at different concentrations of polyethylene glycol (PEG) coincided with each other. C_LIO_LISimilar pH profiles were also obtained for E. coli DH5 growth in LB medium with different PEG concentrations. C_LIO_LIHowever, PEG exerted toxicity effect on Bacillus subtilis NRS-762 during growth in LB medium at 30 {degrees}C, with reduction of biomass formation in a dose dependent manner. C_LIO_LISimilar to the case for E. coli DH5. pH profiles of B. subtilis NRS-762 coincided with each other irrespective of the concentrations of PEG used. C_LI

microbiology↗
bioRxiv2020

Ribosomal proteins could explain the phylogeny of Bacillus species

Protein translation is a highly conserved process in biology. As participants of translation, ribosomal proteins in the large and small subunits of the ribosomes are likely to be highly conserved; thus, could they be endowed with sufficient sequence diversity to chronicle the evolutionary history of different species in the same or different genus? Using different Bacillus species as a model system, this study sought to examine if ribosomal proteins could reproduce the maximum likelihood phylogeny described by 16S rRNA of the investigated Bacillus species. Bacillus species investigated were Bacillus amyloliquefaciens, Bacillus cereus, Bacillus licheniformis, Bacillus megaterium, Bacilluspumilus, Bacillus subtilis, and Bacillus thuringiensis. Results revealed that ribosomal proteins could be categorized into four different groups depending on their extent in reproducing the 16S rRNA phylogeny of the different Bacillus species. The first group comprises ribosomal protein that could reproduce all the phylogenetic positions of the Bacillus species accurately. These ribosomal proteins were ribosomal protein L6, L7/12, L9, L13, L24, L32, S3, S9, S12, S15, S16, S17, and S18. Ribosomal proteins that hold partial phylogenetic significance constitutes the second group where the ribosomal proteins could reproduce the major branches of the 16S rRNA phylogenetic tree but differ in the placement of one or two Bacillus species. In general, this group of ribosomal proteins had difficulty differentiating B. licheniformis and B. pumilus at the sequence level. Members of this group of ribosomal protein include ribosomal protein L22, L29, L30, L31 Type B, L33, L35, S1, S4, S5, S6, S7, S8, S11, S13, S19, and S20. The third group of ribosomal proteins were those which were highly conserved at the sequence level, and which could not differentiate the different Bacillus species. These ribosomal proteins were ribosomal protein L5, L36, S2, S10, and S21. Finally, there were also ribosomal proteins that randomly placed the different Bacillus species into phylogenetic positions not in sync with those depicted by the 16S rRNA phylogenetic tree. These ribosomal proteins were ribosomal protein L7Ae, L17, L20, L23, L27, L28, L31, L34 and S14 Type Z. Overall, members of all four groups of ribosomal proteins came from both the large and small ribosome subunits which meant that evolutionary forces exerted selective pressure on both subunits but at differing extents. Collectively, specific ribosomal proteins could reproduce the phylogeny of different Bacillus species as described by the gold standard phylogenetic marker, 16S rRNA, which highlighted that co-evolutionary processes could be at work in shaping the evolution of ribosomal proteins and rRNA in close contact with each other in the ribosome. Subject areasecology, biochemistry, biotechnology, microbiology, cell biology Significance of the work16S rRNA is the gold standard phylogenetic marker used to inform the evolutionary relationships between different species across the three domains of life. Given that 16S rRNA is nestled in the ribosomes together with a consortium of ribosomal proteins each with unique structural and enzymatic functions, could ribosomal proteins be used similarly as phylogenetic markers for informing species divergence and relationships? Specifically, as part of the highly conserved ribosome important to protein translation, do ribosomal proteins possess sufficient sequence diversity to help chronicle the evolutionary relationships between different species? By reconstructing the maximum likelihood phylogenetic tree of different Bacillus species, this study revealed that ribosomal proteins fall into four categories concerning their utility for informing phylogeny between different species of the same genus. Specifically, there existed ribosomal proteins able to accurately reproduce the phylogenetic tree described by 16S rRNA. On the other hand, there were ribosomal proteins that hold only partial phylogenetic significance where they could reproduce the major branches of the reference phylogenetic tree but differ in the placement of one or two species along the tree. Besides the above two categories, they were also ribosomal proteins whose sequence diversity was not sufficient to help differentiate between different Bacillus species. Finally, another class of ribosomal proteins did not chronicle the evolutionary trajectories of the different species resulting in phylogenetic tree with random placement of the different species. Overall, evolutionary forces likely exerted different selection forces on different ribosome subunits as well as individual ribosomal protein that resulted in the differentiation of their utility as phylogenetic markers of different species of the same genus. Co-evolution between ribosomal proteins as well as between ribosomal proteins and rRNA might underpin part of the evolutionary history chronicled by individual ribosomal proteins, thereby, endowing them with phylogenetic significance. HighlightsO_LIRibosomal proteins were found to be useful in describing the phylogeny of different Bacillus species compared to the gold standard phylogenetic marker, 16S rRNA. C_LIO_LIBy examining the maximum likelihood phylogenetic tree reconstructed, ribosomal proteins could be categorized into four groups with differing phylogenetic significance. C_LIO_LIThe first group comprises ribosomal proteins able to accurately reproduce all the phylogenetic positions of different Bacillus species relative to 16S rRNA phylogenetic tree. This group include ribosomal protein L6, L7/12, L9, L13, L24, L32, S3, S9, S12, S15, S16, S17, and S18. C_LIO_LIThe second group refers to ribosomal proteins able to reproduce the major branches of the 16S rRNA phylogenetic tree but lacks in the correct placement of one or two Bacillus species. These ribosomal proteins were L22, L29, L30, L31 Type B, L33, L35, SI, S4, S5, S6, S7, S8, Sll, S13, S19, and S20. C_LIO_LIThe third group of ribosomal proteins are ones with highly conserved sequence unable to differentiate between different Bacillus species. It comprised ribosomal proteins L5, L36, S2, S10, and S21. C_LIO_LIThe final group of ribosomal proteins did not chronicle the evolutionary forces acting on the different Bacillus species and generated phylogenetic trees with random placement of the different Bacillus species. These ribosomal proteins were L7Ae, L17, L20, L23, L27, L28, L31, L34 and S14 Type Z. C_LI

evolutionary biology↗
bioRxiv2020

Annotation of ribosomal protein mass peaks in MALDI-TOF mass spectra of bacterial species and their phylogenetic significance

Although MALDI-TOF mass spectrometry based microbial identification has achieved a level of accuracy that facilitate its use in classifying microbes to the species and strain level, questions remain on the identities of the mass peaks profiled from individual microbial species. Specifically, in the popular approach of comparing the mass spectrum of known and unknown microbes for identification purposes, the identities of the mass peaks were not taken into consideration. This study sought to determine if ribosomal proteins could account for some of the mass peaks profiled in MALDI-TOF mass spectra of different bacterial species. Using calculated molecular mass of ribosomal proteins for annotating mass peaks in bacterial species MALDI-TOF mass spectra downloaded from the SpectraBank database, this study revealed that ribosomal proteins could account for the low molecular weight mass peaks of <10000 Da. However, contrary to published reports, ribosomal proteins could not account for most of the mass peaks profiled. In particular, the data revealed that between 1 and 6 ribosomal protein mass peaks could be annotated in each mass spectrum. Annotated ribosomal proteins were S16, S17, S18, S20 and S21 from the small ribosome subunit, and L27, L28, L29, L30, L31, L31 Type B, L32, L33, L34, L35 and L36 from the large ribosome subunit. The ribosomal proteins with the most number of mass peak annotations were L36 and L29, with L34, L33, and L31 completing the list of ribosomal proteins with large number of annotations. Given the highly conserved nature of most ribosomal proteins, possible phylogenetic significance of the annotated ribosomal proteins were investigated through reconstruction of maximum likelihood phylogenetic trees. Results revealed that except for ribosomal protein L34, L31, L36 and S18, all annotated ribosomal proteins hold phylogenetic significance under the criteria of recapitulation of phylogenetic cluster groups present in the phylogeny of 16S rRNA. Phylogenetic significance of the annotated ribosomal proteins was further verified by the phylogenetic tree constructed based on the concatenated amino acid sequence of L29, S16, S20, S17, L27 and L35. Finally, analysis of the structure of the annotated ribosomal proteins did not reveal a high conservation of structure of the ribosomal proteins. Collectively, small low molecular weight (<10000 Da) ribosomal proteins could annotate some of the mass peaks in MALDI-TOF mass spectra of various bacterial species, and most of the ribosomal proteins hold phylogenetic significance. However, structural analysis did not identify a conserved structure for the annotated ribosomal proteins. Annotation of ribosomal protein mass peaks in MALDI-TOF mass spectra highlighted the deep biological basis inherent in the mass spectrometry-based microbial identification method. Subject areas biochemistry, biotechnology, microbiology, evolution, ecology Significance of the workWhile MALDI-TOF MS has been successfully used in identification of different microbes to the species and strain level through the comparison of mass spectra of known and unknown microbes, the approach (known as mass spectrum fingerprinting) remains lacking in the biological basis that underpins the technique. This study sought to uncover some of the biological basis that underpins MALDI-TOF MS microbial identification through the annotation of profiled mass peaks with ribosomal proteins. Previous studies have linked different ribosomal proteins to mass peaks in MALDI-TOF mass spectra of bacteria; however, broad spectrum verification of the finding across multiple species across different genera remain lacking. Using a collection of MALDI-TOF mass spectra of 110 bacterial species and strains catalogued in SpectraBank, this study sought to annotate ribosomal protein mass peaks in the mass spectra. Results revealed that small, low molecular weight ribosomal proteins of molecular mass < 10000 Da could annotate between 1 and 6 mass peaks in the catalogued mass spectra. This was smaller than the number of ribosomal proteins mass peaks postulated by previous studies. Overall, 16 ribosomal proteins (S16, S17, S18, S20, S21, L27, L28, L29, L30, L31, L31 Type B, L32, L33, L34, L35, and L36) were annotated with the most number of mass peaks annotations coming from L36 and L29. Reconstruction of phylogenetic trees of the annotated ribosomal proteins revealed that most of the ribosomal proteins hold phylogenetic significance with respect to the phylogeny of 16S rRNA. This provided further evidence that a deep biological basis is present in the approach of using mass spectrometry profiling of biomolecules for identifying bacterial species. HighlightsO_LIRibosomal protein mass peaks were annotated in MALDI-TOF mass spectra of bacterial species across multiple genera. C_LIO_LIAnnotated ribosomal proteins were S16, S17, S18, S20, S21 for the small ribosome subunit, and L27, L28, L29, L30, L31, L31 Type B, L32, L33, L34, L35, L36 for the large ribosome subunit. C_LIO_LIBetween 1 and 6 ribosomal protein mass peaks were annotated per mass spectrum, a number significantly lower than that implied by other studies. C_LIO_LIAnnotated ribosomal proteins were small, low molecular weight ribosomal proteins of molecular mass < 10000 Da. C_LIO_LIPhylogenetic tree reconstruction revealed the phylogenetic significance of most annotated ribosomal proteins except ribosomal protein L34, L31, L36 and S18. C_LIO_LIMulti-locus sequence typing of L29, S16, S20, S17, L27 and L35 further showed the phylogenetic significance of ribosomal proteins in recapitulating the phylogeny of 16S rRNA. C_LIO_LIStructural analysis of annotated ribosomal proteins did not find conserved structure. Thus, the reasons for the annotation of particular ribosomal proteins over others remain unknown. C_LI

bioinformatics↗
bioRxiv2020

Number of mismatches and length of longest match correlate with alignment score in swalign built-in function in MATLAB

Understanding how one sequence relates to another at the nucleotide or amino acid level allows the derivation of new knowledge regarding the provenance of particular sequence as well as the determination of consensus sequence motifs that informs biological conservation at the sequence level. To this end, local or multiple sequence alignments tools in bioinformatics have been developed to automatically profile two or more nucleotide or amino acid sequence in search of matches in stretches of nucleotides or amino acid sequence that yield an alignment. While alignment score is a common metric for assessing alignment quality, relative difference between alignment scores does not readily correlate with concrete measures such as number of mismatches and length of longest match in alignment. Thus, using swalign local sequence alignment function in MATLAB on 200 alignments between RNA-seq sequence read and reference Escherichia coli K-12 MG1655 genome sequence in the sense and antisense direction, this work sought to shed some light on how alignment score from swalign correlates with number of mismatches and length of longest match. Results revealed that number of mismatches negatively correlate with alignment score; thereby, validating theoretical predictions that larger number of mismatches would result in a poorer alignment and lower alignment score. However, dependence of alignment score on other factors such as length of longest match and gap penalty from opening an alignment gap prevents linear relationship to be obtained between number of mismatches and alignment score. On the other hand, length of longest match was found to positively correlate with alignment score as predicted from theoretical understanding. But, data obtained revealed that clusters of data points gather at two regions of the scatter plot involving short matches and low alignment score, as well as long matches and high alignment score. Such clustering and sparseness of data points between the two clusters preclude the elucidation of a linear quantitative relationship between length of longest match and alignment score. Overall, dependence of alignment score of swalign on number of mismatches and length of longest match in alignment match theoretical predictions; thereby, validating the utility of alignment score in indicating the qualitative quality of alignment. However, given that alignment score inherently depends on a multitude of factors, users could not easily discern the quantitative difference in mismatches and length of longest match from relative differences between two alignment scores. Such problems are unlikely to be resolved given the near impossibility of obtaining quantitative linear relationship correlating either number of mismatches or length of longest match with alignment score of a sequence alignment tool. HighlightsO_LINumber of mismatches in alignment negatively correlates with alignment score. C_LIO_LILength of longest match positively correlates with alignment score. C_LIO_LIQuantitative linear relationship could not be obtained for alignment score with either number of mismatches or length of longest match. C_LIO_LIResults validate that swalign tool in MATLAB could quantitatively detect differences in alignment quality and expressed it using alignment score. C_LIO_LIBut, relative alignment score of two alignments remains a nebulous concept with regards to differences in number of mismatches and length of longest match. C_LI

bioinformatics↗