Biology subjects

Ng, W.

Publications and source records attributed to Ng, W..

12 recordsLinked to original sources

bioRxiv2025

Phaeochromocytomas and paragangliomas harbour tumour-initiating SOX2+ stem cells

Phaeochromocytomas (PCCs) and paragangliomas (PGLs), are rare neuroendocrine tumours that arise in the neural crest (NC)-derived adrenal medulla and the paraganglia, respectively. Approximately 10%-15% of patients with PCCs and 35%-40% with PGLs go on to develop metastatic disease, leading to a reported median overall survival of 7 years. The development of prognostic markers and subsequent personal therapeutic strategies are hindered by a lack of understanding of tumourigenesis. In other organs, cells with stem-like properties are at the root of tumour initiation and maintenance, due to their ability to self- renew and give rise to differentiated cells. We have recently shown that, in the human adrenal, a subset of sustentacular cells, endowed with a support role, are in fact SOX2+ postnatal adrenomedullary stem cells, that are specified along the neural crest migratory route. In this study, we intended to determine if SOX2+ cells in PCCs and PGLs can behave as tumour-initiating stem cells. Using expression and transcriptomic studies, we demonstrate the presence of SOX2/SOX2-expressing cells across a broad range of PCCs and PGLs, irrespective of tumour aggressiveness, location, and causative mutation. In silico analyses reveal the co-expression of SOX2 and chromaffin cell markers in the tumour, and the active proliferation of these double-positive cells. Isolation of these cells in vitro in stem cell-promoting media, and their xenotransplantation on chicken chorioallantoic membranes, demonstrates that they have the potential to expand and metastasise in ovo, supporting their potential as tumour-initiating cells.

cancer biology↗

bioRxiv2022

Statistical analysis of number of genes and chromosome lengths of different microbial species

Genome architecture concerns the organisation of genes on a chromosome, and has important implications to the fidelity in which genes are encoded on the chromosome, and how the information is read by DNA polymerase and RNA polymerase. This facet of genomics did receive attention in the early epoch of genomics, but it has received less attention in contemporary genomics as attention shifts to structural and functional genomics with the goal of annotating the function of each gene in the genome. This work sought to uncover relationships between number of genes and chromosome length in a variety of bacteria and archaea species as a preamble to understanding the prevalence and importance of repetitive sequences in the genome of prokaryotic species. Aggregate results with the ensemble of prokaryotic species profiled revealed a positive linear correlation between number of genes and chromosome length. Upon dissection into the Bacteria and Archaea domains, the linear relationship described above still stands for Bacteria but starts to break down in Archaea. This suggests that repetitive sequences are more important to Archaea species, which generally have a smaller genome (1.8 to 2.8 Mbp) and fewer genes (1500 to 2400) compared to bacterial species. In comparison, the bacterial genome is larger (4 to 5.6 Mbp), and encodes more genes (3600 to 5100). Overall, the results highlight that bacterial genome are efficiently encoded with few repetitive sequences. This, however, is not true for archaeal genome, which provides another line of evidence supporting the notion that archaea are ancestral eukaryotic cells, which like the archaea also houses large repetitive sequences. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=141 SRC="FIGDIR/small/503871v1_ufig1.gif" ALT="Figure 1"> View larger version (15K): org.highwire.dtl.DTLVardef@1632506org.highwire.dtl.DTLVardef@13e91forg.highwire.dtl.DTLVardef@12e1316org.highwire.dtl.DTLVardef@1e7381e_HPS_FORMAT_FIGEXP M_FIG C_FIG Short descriptionStatistical analysis across an ensemble of 59 microbial species revealed a strong linear correlation between number of genes and chromosome length. This suggests that prokaryotic genomes are highly compact with genes, and do not carry significant amounts of repeats unlike the case in eukaryotic organisms. The result holds significant implications for our understanding of genome evolution and compaction in prokaryotic organisms, and what drove their accession as foundational species of many ecosystems. Subject areasgenomics, molecular biology, evolutionary biology, bioinformatics, systems biology,

genomics↗

bioRxiv2021

Ribosomal protein database profiling lends clarity to ribosomal protein evolution and mass distribution

Existence of theoretical ribosomal protein mass fingerprint as well as utility of ribosomal protein as biomarkers in mass spectrometry microbial identification suggests phylogenetic significance for this class of proteins. To serve the above two functions, facile means of identifying and extracting important attributes of ribosomal proteins from proteome data file of microbial species must be found. Additionally, there is a need to calculate important properties of ribosomal proteins such as molecular weight and nucleotide sequence based on amino acid sequence information from FASTA proteome file. This work sought to support the above endeavour through developing a MATLAB software that extracts the amino acid sequence information of all ribosomal proteins from the FASTA proteome datafile of a microbial species downloaded from UniProt. Built-in functions in MATLAB are subsequently employed to calculate important properties of extracted ribosomal proteins such as number of amino acid residue, molecular weight and nucleotide sequence. All information above are output, as a database, to an Excel file for ease of storage and retrieval. Data available from the analysis of an Escherichia coli K-12 proteome revealed that the bacterium possess a total of 59 ribosomal proteins distributed between the large and small ribosome subunits. The ribosomal protein ranges in sequence length from 38 (50S ribosomal protein L36) to 557 (30S ribosomal protein S1). In terms of molecular weight distribution, the profiled ribosomal proteins range in weight from 4364.305 Da (50S ribosomal protein L36) to 61157.66 Da (30S ribosomal protein S1). More important, analysis of the distribution of the molecular weight of different ribosomal proteins in E. coli reveals a smooth curve that suggests strong co-evolution of ribosomal protein sequence and mass given the tight constraints that a functional ribosome presents. Finally, cluster analysis reveals a preponderance of small ribosomal proteins compared to larger ones, which remains to be a mystery to evolutionary biologists. Overall, the information encapsulated in the ribosomal protein database should find use in gaining a better appreciation for the molecular weight distribution of ribosomal proteins in a species, as well as delivering information for using ribosomal protein biomarkers in identifying particular microbial species in mass spectrometry microbial identification. Subject areasbiochemistry, microbiology, bioinformatics, biotechnology, molecular biology, Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=74 SRC="FIGDIR/small/465821v1_ufig1.gif" ALT="Figure 1"> View larger version (11K): org.highwire.dtl.DTLVardef@17b8205org.highwire.dtl.DTLVardef@195517eorg.highwire.dtl.DTLVardef@1940a0org.highwire.dtl.DTLVardef@1e1ea47_HPS_FORMAT_FIGEXP M_FIG C_FIG Short descriptionSmooth function describes the distribution of molecular weight of ribosomal proteins in Escherichia coli, which suggests strong co-evolution pressure that fine-tunes the molecular weight of individual proteins with the constraint coming from the overall structure of the ribosome that needs to deliver a consistent function to the living cell. Multitude of ribosomal proteins with different roles in the ribosomal proteins under tight co-evolution pressure likely engender the observed smooth curve in the above plot. O_TEXTBOXHighlightsO_LIAutomated MATLAB software for extracting ribosomal protein sequence from FASTA proteome file of a microbial species was developed. C_LIO_LIIn-built functions were used to calculate nucleotide sequence, number of residues and molecular weight of each of the extracted ribosomal protein C_LIO_LIAll extracted and calculated information were encapsulated as a ribosomal protein database for output to an Excel file for ease of storage and retrieval. C_LIO_LIInformation in database could be useful for theoretical ribosomal protein mass fingerprint or help assign ribosomal protein biomarker peaks in matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF MS) microbial identification. C_LI C_TEXTBOX

bioinformatics↗

bioRxiv2021

Categorization of prophage genes in Bacillus subtilis 168 and assessing their relative importance through RNA-seq gene expression analysis

Bacteriophage evolves to control the population of fast-growing bacterial cells, without which explosion in bacterial population may induce unimaginable harm to diverse ecosystems. But, bacteriophage also "hide" in bacterial genomes when nutritional and environmental circumstances are unfavourable. This involves the integration of phage genome into the host genome at appropriate genomic loci in a process known as lysogeny. This work sought to delineate the prophages present in the annotated genome of Bacillus subtilis 168, and assess their relative importance through RNA-seq expression analysis. Firstly, examination of the annotated genome of the model Gram-positive bacterium revealed five distinct prophage regions: SPBeta, prophage 6, PBSX, prophage 3 region, and prophage 1 region. All prophage regions contain host genes, which suggests that host transposase activity have swapped in host genes for phage genes in the prophage genome. Given the significant number of phage genes that have been swapped into each of the prophage genome, all prophage regions are deemed to be defective. BLAST analysis further highlighted that many of the prophages in B. subtilis are extinct given that they do not have ancestral or daughter brethren. However, RNA-seq transcriptome analysis of B. subtilis turned out an interesting paradox indicative of the important role that host transposase have in swapping in host promoters for prophage genes. Specifically, a significant number of prophage genes are highly expressed, which is implausible given that phage genes should be transcriptionally silent. The result and phenomenon further suggests the relative facile nature in which host promoters could be swapped in for phage genes, which is indicative of presence of genomic motifs in prophage genome recognizable by host transposase. Existence of such sequence motifs is thus indicative of possible co-evolution of transposase and phages where transposases were originally a part of the phage genome, which latter "jumped out" into the host genome to aid the swapping in of host genes into the prophage genome for augmenting prophage genetic repertoire in the face of changing environmental conditions. Overall, it is not uncommon for bacterial species to harbour multiple prophages. But, lysogeny may not be a viable option for long-term preservation of prophage genetic repertoire given that host transposase would inevitable swap in host genes at random locations in the prophage genome.

bioinformatics↗

bioRxiv2021

Developing an ethanol utilisation pathway based NADH regeneration system in Escherichia coli

Many industrially relevant biotransformation in whole-cells are dependent on cofactors such as NADH or NADPH. Cofactor regeneration is an established approach for providing a cheap source of cofactors in support of the main biotransformation reaction in biocatalysis. In essence, cofactor regeneration uses a sacrificial substrate to help regenerate a cofactor consumed by the main biotransformation reaction. Enzymatic in nature, alternative cofactor regeneration systems with high efficiency and which utilises low cost sacrificial substrate are of interest. Glucose dehydrogenase system has been dominant in NADH regeneration. But, in its current incarnation, glucose dehydrogenase system is relatively inefficient in regenerating NADH with theoretical yield of one NADH per glucose molecule. This work sought to explore the utility of a two-gene ethanol utilisation pathway in NADH regeneration. Comprising the first step that takes ethanol to acetaldehyde, and a second step that converts acetaldehyde to acetyl-CoA, NADH from both steps could be mined for supporting biotransformation reaction in cofactor regeneration mode. Theoretically, ethanol utilisation pathway (EUP) affords a higher NADH yield of two NADH per ethanol molecule, and is therefore more efficient than glucose dehydrogenase (GDH) system. In this project, the EUP pathway was coupled to a cpsADH (an alcohol dehydrogenase from Candida parapsilosis) mediated ketone to alcohol anaerobic biotransformation with concentration of alcohol product as marker for efficiency of cofactor regeneration. Experiment tests showed that EUP was more efficient than GDH. Further, EUP could support biotransformation of both butanone and acetophenone in single and two-phase biotransformation, respectively. Additional work conducted to improve biotransformation efficiency revealed that ethanol provision positively correlated with biotransformation efficiency. Growing cell biotransformation was also found to improve biotransformation efficiency compared to resting cell due largely to the driving force generated by cell growth. Tests of a growth medium effect also found that cells cultivated in M9 ethanol medium delivered higher biotransformation efficiency compared to those cultivated in LB medium. This could arise due to the lower expression of NADH dependent enzymes during growth in M9 ethanol medium compared to LB medium that allowed more NADH to be diverted to support ketone biotransformation. However, a persistent problem with the experimental system is the relatively poor consumption of ethanol that points to need for further engineering of the system. Collectively, pathway-based NADH regeneration is possible with ethanol utilisation, with biotransformation efficiency dependent on mode of biotransformation (resting cell versus growing cell) and growth medium used.

bioengineering↗

bioRxiv2020

Understanding the compositional changes in LB Lennox medium during growth of Escherichia coli DH5α in a 1L bioreactor

Compositional changes in growth medium represents dynamic interplay between cell growth, biomass formation, and energy maintenance, with concomitant decrease in nutrients and increase in secreted metabolites and metabolic byproducts. Such information is important for quantifying microbial physiological response both at the population and cellular level, with respect to understanding subtle differences in microbial growth response, as well as supporting model building efforts in metabolic engineering. With the desire to understand molecular weight changes in components of LB Lennox medium as well as broth fractions present during cultivation of Escherichia coli DH5 (ATCC 53868) at 37 {degrees}C, 400 rpm stirring and 1 VVM aeration in a 1 L bioreactor, this study used a combination of gel filtration chromatography (GFC) and reversed phase high performance liquid chromatography (RP-HPLC) for determining changes to molecular weight of different fractions of the growth medium. Experiment results revealed the difficulty of fractionating the culture broth with RP-HPLC, where no distinct peaks of narrow retention time width were obtained. More importantly, the column used for GFC was unable to differentiate small molecular weight changes on the order of a few tens to few hundred Da through a refractive index detector. Together, GFC and RP-HPLC highlighted the difficulty of fractionating LB Lennox culture broth into different distinct fractions. Finally, the study validated the use of 194 nm as detection wavelength for visualizing the chromatogram of LB Lennox medium eluted from a C-18 reversed phase column during liquid chromatography. Collectively, GFC and RP-HPLC could not fractionate LB Lennox broth of E. coli DH5 into distinct fractions for further analysis by identification techniques such as mass spectrometry. Given the inherent complexity of complex medium such as LB Lennox, clean separation of the medium into every component with high purity may be impossible. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=47 SRC="FIGDIR/small/311373v1_ufig1.gif" ALT="Figure 1"> View larger version (7K): org.highwire.dtl.DTLVardef@2d0861org.highwire.dtl.DTLVardef@814ebcorg.highwire.dtl.DTLVardef@158328borg.highwire.dtl.DTLVardef@15e6844_HPS_FORMAT_FIGEXP M_FIG C_FIG Short descriptionBroad elution profile and lack of distinct peaks in chromatogram of LB Lennox broth at 6 hours post inoculation with Escherichia coli DH5 (ATCC 53868), after attempted fractionation by C-18 reversed phase high performance liquid chromatography (RP-HPLC), revealed that separation could not be achieved with a complex mixture such as a microbiology broth. Specifically, while the objective of understanding compositional changes to culture medium during growth presents tremendous opportunities for determining the dynamic conversion of nutrients into metabolites and byproducts, difficulty of profiling all chemical constituents in a complex broth mixture meant that current model building efforts for metabolic engineering remains primitive with respect to the consortia of metabolic reactions occurring in situ at the cellular level. Subject areasbiotechnology, biochemistry, cell biology, microbiology, analytical chemistry

biochemistry↗

bioRxiv2020

Attempted fractionation of LB Lennox medium via reversed phase high performance liquid chromatography

Mass balance analysis is a highly useful tool for chemical engineering analysis of biological processes. Specifically, composition and amounts of inputs to a cell could be correlated with measurement of metabolic byproducts and outputs for inferring metabolic fluxes flowing through specific cellular metabolic pathways. However, the composition of many common microbiological growth medium remains ill-defined with batch-to-batch variation. Thus, a need exists for developing methods for effective fractionation and separation of common growth medium. Using 5 g/L yeast extract, 10 g/L tryptone, and LB Lennox medium as model systems, this work attempted the fractionation of the three complex growth mixtures using C-18 reversed phase high performance liquid chromatography (RP-HPLC). Results revealed no effective fractionation of the three mixtures. More importantly, experiment results indicated that appropriate choice of detection wavelength for visualizing the chromatogram made a huge difference to understanding the effectiveness of fractionation achieved. Specifically, in the case of yeast extract, tryptone and LB Lennox medium, 194 nm may be a more appropriate detection wavelength compared to 280 nm. Collectively, C-18 RP-HPLC was not effective in separating 5 g/L yeast extract, 10 g/L tryptone and LB Lennox medium with hydrophilic mobile phases (ethanol/water mixture). Graphical abstract O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY Short description: Visualization of the reversed phase HPLC chromatogram at 194 nm revealed broad peaks and lack of distinct peaks indicative of fractionation of LB Lennox medium by the chromatography method. More importantly, complex ensemble of different components in the growth medium present a significant separation challenge that precludes separation or fractionation by modern liquid chromatography methods. Overall, combinatorial use of both hydrophobic and hydrophilic mobile phase with a C-18 reversed phase column could reveal the presence of a couple of main fractions in a mixture otherwise unable to be separated into distinct components. C_FIG_DISPLAY

biochemistry↗

bioRxiv2020

ICP-MS analysis of metal and metalloid concentrations of common microbiological growth media reveals presence of heavy metals

Trace elements such as cobalt and manganese play important roles as cofactors of enzymes, and thus, they collectively impact on biochemistry and cellular metabolism. Hence, it is of importance to gain an understanding of the trace metal and metalloid concentrations of growth medium in order to fully account for the growth performance of the bacterium. But, this aspect of microbial cell cultivation is usually neglected. Advent of instrumented techniques for metals and metalloid analysis such as inductively coupled plasma mass spectrometry (ICP-MS) has significantly facilitated trace element analysis at the parts per billion (ppb) to parts per million (ppm) level in aqueous matrixes free of organic interference. In this work, ICP-MS was utilized as the principal tool for profiling the range of metals and metalloids in different microbiological growth medium ranging from minimal salts medium to complex chemically undefined medium. Growth media examined include: LB Lennox, LB Lennox + 2 g/L glucose, LB Lennox (buffered, 89 mM phosphate), LB Lennox (buffered, 89 mM phosphate) + 6 g/L glucose, formulated medium + 6 g/L glucose, Tryptic Soy Broth, M9 medium, and M9 + 1 g/L yeast extract medium. Results reveal detection of elevated concentrations of chromium, copper and cadmium in different versions of LB Lennox and Tryptic Soy Broth. Concentrations of the above heavy metals in the tens of ppm range meant that the growth media could only support the growth of environmental bacteria with some resistance to heavy metal toxicity. On the other hand, no heavy metals were detected in M9 minimal salts medium or a modified version with supplementation of 1 g/L yeast extract. This indicated that minimal salts media may have less of a problem with heavy metal contamination compared to chemically undefined microbiological growth media. Collectively, the results highlight the essentiality of conducting a comprehensive profiling experiment for detecting different metals and metalloids at trace levels in microbiological growth medium. Such data would in addition to offering a deeper understanding of some peculiar growth behaviour from some microorganisms, may also help identify contamination issue during manufacture that preclude use of the media in cultivating many laboratory domesticated microorganisms. Subject areasbiochemistry, biotechnology, cell biology, microbiology, biochemical engineering,

microbiology↗

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

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