PeerJ Preprints: Bioengineeringhttps://peerj.com/preprints/index.atom?journal=peerj&subject=420Bioengineering articles published in PeerJ PreprintsThe investigation of 2D monolayers as potential chelation agents in Alzheimer’s diseasehttps://peerj.com/preprints/279422019-11-202019-11-20Neha PavuluruXuan Luo
In this study, we conducted Density Functional Theory calculations comparing the binding energy of the copper- Amyloid-beta complex to the binding energies of potential chelation materials. We used the first-coordination sphere of the truncated high-pH Amyloid-beta protein subject to computational limits. Binding energy and charge transfer calculations were evaluated for copper’s interaction with potential chelators: monolayer boron nitride, monolayer molybdenum disulfide, and monolayer silicene. Silicene produced the highest binding energies to copper, and the evidence of charge transfer between copper and the monolayer proves that there is a strong ionic bond present. Although our three monolayers did not directly present chelation potential, the absolute differences between the binding energies of the silicene binding sites and the Amyloid-beta binding site were minimal proving that further research in silicene chelators may be useful for therapy in Alzheimer’s disease.
In this study, we conducted Density Functional Theory calculations comparing the binding energy of the copper- Amyloid-beta complex to the binding energies of potential chelation materials. We used the first-coordination sphere of the truncated high-pH Amyloid-beta protein subject to computational limits. Binding energy and charge transfer calculations were evaluated for copper’s interaction with potential chelators: monolayer boron nitride, monolayer molybdenum disulfide, and monolayer silicene. Silicene produced the highest binding energies to copper, and the evidence of charge transfer between copper and the monolayer proves that there is a strong ionic bond present. Although our three monolayers did not directly present chelation potential, the absolute differences between the binding energies of the silicene binding sites and the Amyloid-beta binding site were minimal proving that further research in silicene chelators may be useful for therapy in Alzheimer’s disease.Geobacter protein nanowireshttps://peerj.com/preprints/277732019-06-022019-06-02Derek R LovleyDavid J F Walker
The study of electrically conductive protein nanowires in Geobacter sulfurreducens has led to new concepts for long-range electron extracellular transport, as well as the development of sustainable conductive materials and electronic devices with novel functions. Until recently, electrically conductive pili (e-pili), assembled from the PilA pilin monomer, were the only known Geobacter protein nanowires. However, filaments comprised of the multi-heme c-type cytochrome, OmcS, are present in some preparations of G. sulfurreducens outer-surface proteins. The purpose of this review is to evaluate the available evidence on the in vivo expression of e-pili and OmcS filaments and their biological function. Abundant literature demonstrates that G. sulfurreducens expresses e-pili, which are required for long-range electron transport to Fe(III) oxides and through conductive biofilms. In contrast, there is no definitive evidence yet that wild-type G. sulfurreducens express long filaments of OmcS extending from the cells, and deleting the gene for OmcS actually increases biofilm conductivity. The literature does not support the concern that many previous studies on e-pili were mistakenly studying OmcS filaments. For example, heterologous expression of the aromatic-rich pilin monomer of G. metallireducens in G. sulfurreducens increases the conductivity of individual nanowires more than 5000-fold, whereas expression of an aromatic-poor pilin reduced conductivity more than 1000-fold. This more than million-fold range in nanowire conductivity was achieved while maintaining the 3 nm diameter consistent with e-pili, not OmcS. Purification methods that eliminate all traces of OmcS yield highly conductive e-pili. Substantial evidence suggests that OmcS is often associated with the outer cell surface and intermittently localized along e-pili in vivo. Future studies of G. sulfurreducens expression of protein nanowires need to be cognizant of the importance of maintaining environmentally relevant growth conditions because artificial laboratory culture conditions can rapidly select against e-pili expression. Principles derived from the study of e-pili have enabled identification of non-cytochrome protein nanowires in diverse bacteria and archaea. A similar search for cytochrome appendages is warranted. Both e-pili and OmcS filaments offer design options for the synthesis of protein-based ‘green’ electronics, which may be the primary driving force for the study of these structures in the near future.
The study of electrically conductive protein nanowires in Geobacter sulfurreducens has led to new concepts for long-range electron extracellular transport, as well as the development of sustainable conductive materials and electronic devices with novel functions. Until recently, electrically conductive pili (e-pili), assembled from the PilA pilin monomer, were the only known Geobacter protein nanowires. However, filaments comprised of the multi-heme c-type cytochrome, OmcS, are present in some preparations of G. sulfurreducens outer-surface proteins. The purpose of this review is to evaluate the available evidence on the in vivo expression of e-pili and OmcS filaments and their biological function. Abundant literature demonstrates that G. sulfurreducens expresses e-pili, which are required for long-range electron transport to Fe(III) oxides and through conductive biofilms. In contrast, there is no definitive evidence yet that wild-type G. sulfurreducens express long filaments of OmcS extending from the cells, and deleting the gene for OmcS actually increases biofilm conductivity. The literature does not support the concern that many previous studies on e-pili were mistakenly studying OmcS filaments. For example, heterologous expression of the aromatic-rich pilin monomer of G. metallireducens in G. sulfurreducens increases the conductivity of individual nanowires more than 5000-fold, whereas expression of an aromatic-poor pilin reduced conductivity more than 1000-fold. This more than million-fold range in nanowire conductivity was achieved while maintaining the 3 nm diameter consistent with e-pili, not OmcS. Purification methods that eliminate all traces of OmcS yield highly conductive e-pili. Substantial evidence suggests that OmcS is often associated with the outer cell surface and intermittently localized along e-pili in vivo. Future studies of G. sulfurreducens expression of protein nanowires need to be cognizant of the importance of maintaining environmentally relevant growth conditions because artificial laboratory culture conditions can rapidly select against e-pili expression. Principles derived from the study of e-pili have enabled identification of non-cytochrome protein nanowires in diverse bacteria and archaea. A similar search for cytochrome appendages is warranted. Both e-pili and OmcS filaments offer design options for the synthesis of protein-based ‘green’ electronics, which may be the primary driving force for the study of these structures in the near future.Understanding the chemical basis for the preferential ionization of specific biomolecules in mass spectrometry analysis of microbial cellshttps://peerj.com/preprints/277592019-05-262019-05-26Wenfa Ng
Mass spectrometry-enabled microbial identification has successfully demonstrated the feasibility of using profiled biomolecules for identifying microorganisms based on a chemometric or proteome database search approach. However, mechanisms driving the preferential ionization and detection of particular biomolecules in various types of mass spectrometry remain poorly understood. Specifically, mass spectra obtained from different microbial species remain poorly annotated with respect to the specific types of biomolecules accounting for the peaks. For example, while ribosomal proteins are known to be a significant class of biomolecules that could partially account for the profiled mass peaks in mass spectra of microorganisms, other classes of proteins and biomolecules remain poorly annotated. This raises the important question of how different mass spectrometry approaches ionize different types of biomolecules from a cellular matrix. Specifically, mass spectra of microorganisms reveal that only a couple of mass peaks could capture the phylogeny of a species. However, the proteome of a cell is much larger and more complicated, and yet is not fully profiled by different types of mass spectrometry methods. For example, electrospray ionization mass spectrometry (ESI-MS) and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) could only provide a small snapshot of the entire bacterial proteome. It could be argued that different mass spectrometry methods provide complementary views of a particular proteome. However, the question remains, how do proteins and biomolecules interact with the different sample preparation and mass spectrometry analysis methods for generating an ion cloud for separation in a mass spectrometer? Thus, efforts could be directed towards understanding how different types of proteins could be preferentially ionized by MALDI-TOF MS. Specifically, different reagents could be used to perform chemical pretreatment on the proteome, which would subsequently be analyzed by mass spectrometry. Thus, a correlative map between types of chemical pretreatment used and the corresponding mass spectra could be obtained. Collectively, knowledge gleaned from the research would illuminate the chemical basis by which specific biomolecules are preferentially ionized under particular conditions, which would inform the development of strategies for increasing the subset of biomolecules ionized from a cellular proteome. Such chemical rules would also aid in the interpretation of mass spectra obtained, particularly in understanding the biological context of the experiment. Overall, the key goal of this research is to help answer the question: what is the biological basis and context of the mass spectrum obtained from cells?
Mass spectrometry-enabled microbial identification has successfully demonstrated the feasibility of using profiled biomolecules for identifying microorganisms based on a chemometric or proteome database search approach. However, mechanisms driving the preferential ionization and detection of particular biomolecules in various types of mass spectrometry remain poorly understood. Specifically, mass spectra obtained from different microbial species remain poorly annotated with respect to the specific types of biomolecules accounting for the peaks. For example, while ribosomal proteins are known to be a significant class of biomolecules that could partially account for the profiled mass peaks in mass spectra of microorganisms, other classes of proteins and biomolecules remain poorly annotated. This raises the important question of how different mass spectrometry approaches ionize different types of biomolecules from a cellular matrix. Specifically, mass spectra of microorganisms reveal that only a couple of mass peaks could capture the phylogeny of a species. However, the proteome of a cell is much larger and more complicated, and yet is not fully profiled by different types of mass spectrometry methods. For example, electrospray ionization mass spectrometry (ESI-MS) and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) could only provide a small snapshot of the entire bacterial proteome. It could be argued that different mass spectrometry methods provide complementary views of a particular proteome. However, the question remains, how do proteins and biomolecules interact with the different sample preparation and mass spectrometry analysis methods for generating an ion cloud for separation in a mass spectrometer? Thus, efforts could be directed towards understanding how different types of proteins could be preferentially ionized by MALDI-TOF MS. Specifically, different reagents could be used to perform chemical pretreatment on the proteome, which would subsequently be analyzed by mass spectrometry. Thus, a correlative map between types of chemical pretreatment used and the corresponding mass spectra could be obtained. Collectively, knowledge gleaned from the research would illuminate the chemical basis by which specific biomolecules are preferentially ionized under particular conditions, which would inform the development of strategies for increasing the subset of biomolecules ionized from a cellular proteome. Such chemical rules would also aid in the interpretation of mass spectra obtained, particularly in understanding the biological context of the experiment. Overall, the key goal of this research is to help answer the question: what is the biological basis and context of the mass spectrum obtained from cells?Possibility of tuning the differentiation state of tumor associated macrophages towards tumor controlling phenotypeshttps://peerj.com/preprints/277472019-05-202019-05-20Wenfa Ng
Although various immune cells could infiltrate the cellular and tissue environment surrounding a tumor, the tumor microenvironment nevertheless presents immunosuppressive conditions unfavorable for immune cells to conduct large scale attack on cancer cells. For example, T-cells that make it to the tumor microenvironment are typically non-functional in containing tumor growth. On the other hand, macrophages could infiltrate the tumor microenvironment and is an important cell type modulated by and which also modulates the tumor. Specifically, two variants of macrophages with different phenotypes are known to exhibit close interactions with tumors. Known as M1 and M2 macrophages, they present dichotomously different signals to the tumor. Specifically, M1 macrophages control tumor growth while M2 macrophages promote tumor growth. Thus, from a treatment perspective, it would be desirable to tune the phenotypes and cell differentiation program of macrophages towards the M1 subset. To do that, differential gene expression of macrophages in the M1 and M2 lineages must be understood. Such a goal could be achieved with the profiling of tumor associated macrophages from tumor biopsy samples for gene expression patterns characteristic of the two dominant macrophage lineages. Single cell RNA-sequencing conducted after flow cytometry sorting of M1 and M2 macrophages would highlight gene expression patterns associated with each lineage, and the cellular differentiation programs that prompted entry into particular macrophage subtype. Knowledge of gene expression pattern associated with each macrophage lineage is not useful for tuning their differentiation state unless specific transcription factor that trigger the regulon could be identified. To this end, transcription factors that have been upregulated in the differentiation program could be profiled from the transcriptome data, and help inform the design of vectors for targeted overexpression of specific transcription factor for modulating cellular differentiation of macrophage. Given their low immunogenicity, adeno-associated virus (AAV) could serve as vectors for ferrying the gene cassette containing specific transcription factors into macrophages. Delivery methods for the AAV could be via targeted local infusion of vectors to tumors or through the systemic circulation, but the latter approach would result in lower transfection efficiency. Collectively, possibility exists of tuning the differentiation state of macrophage associated with tumors for enabling tumor controlling lineage to be dominant. Such immuno-targeted therapy would harness the body’s macrophages for controlling tumor growth and represents a treatment option that may yield fewer side effects compared to conventional chemotherapy. But, identification of genes that control lineage-specific differentiation program and the delivery of gene cassette to macrophages for modulating their differentiation remain key challenges.
Although various immune cells could infiltrate the cellular and tissue environment surrounding a tumor, the tumor microenvironment nevertheless presents immunosuppressive conditions unfavorable for immune cells to conduct large scale attack on cancer cells. For example, T-cells that make it to the tumor microenvironment are typically non-functional in containing tumor growth. On the other hand, macrophages could infiltrate the tumor microenvironment and is an important cell type modulated by and which also modulates the tumor. Specifically, two variants of macrophages with different phenotypes are known to exhibit close interactions with tumors. Known as M1 and M2 macrophages, they present dichotomously different signals to the tumor. Specifically, M1 macrophages control tumor growth while M2 macrophages promote tumor growth. Thus, from a treatment perspective, it would be desirable to tune the phenotypes and cell differentiation program of macrophages towards the M1 subset. To do that, differential gene expression of macrophages in the M1 and M2 lineages must be understood. Such a goal could be achieved with the profiling of tumor associated macrophages from tumor biopsy samples for gene expression patterns characteristic of the two dominant macrophage lineages. Single cell RNA-sequencing conducted after flow cytometry sorting of M1 and M2 macrophages would highlight gene expression patterns associated with each lineage, and the cellular differentiation programs that prompted entry into particular macrophage subtype. Knowledge of gene expression pattern associated with each macrophage lineage is not useful for tuning their differentiation state unless specific transcription factor that trigger the regulon could be identified. To this end, transcription factors that have been upregulated in the differentiation program could be profiled from the transcriptome data, and help inform the design of vectors for targeted overexpression of specific transcription factor for modulating cellular differentiation of macrophage. Given their low immunogenicity, adeno-associated virus (AAV) could serve as vectors for ferrying the gene cassette containing specific transcription factors into macrophages. Delivery methods for the AAV could be via targeted local infusion of vectors to tumors or through the systemic circulation, but the latter approach would result in lower transfection efficiency. Collectively, possibility exists of tuning the differentiation state of macrophage associated with tumors for enabling tumor controlling lineage to be dominant. Such immuno-targeted therapy would harness the body’s macrophages for controlling tumor growth and represents a treatment option that may yield fewer side effects compared to conventional chemotherapy. But, identification of genes that control lineage-specific differentiation program and the delivery of gene cassette to macrophages for modulating their differentiation remain key challenges.Off-line and on-line optical monitoring of microalgal growthhttps://peerj.com/preprints/277442019-05-192019-05-19Hugo-Enrique Lazcano-HernandezGabriela AguilarGabriela DzulRodrigo PatiñoJavier Arellano-Verdejo
The growth of Chlamydomonas reinhardtii microalgae cultures was successfully monitored, from classic off-line optical techniques (optical density and fluorescence) to on-line analysis of digital images. In this study, it is shown that the chlorophyll fluorescence ratio F685/F740 has a linear correlation with the logarithmic concentration of microalgae. Moreover, with digital images, the biomass concentration was correlated with: the luminosity of the images through an exponential equation, and the length of penetration of a superluminescent blue beam (λ=440 nm), through an inversely proportional function. Outcomes of this study are useful to monitor both research and industrial microalgae cultures.
The growth of Chlamydomonas reinhardtii microalgae cultures was successfully monitored, from classic off-line optical techniques (optical density and fluorescence) to on-line analysis of digital images. In this study, it is shown that the chlorophyll fluorescence ratio F685/F740 has a linear correlation with the logarithmic concentration of microalgae. Moreover, with digital images, the biomass concentration was correlated with: the luminosity of the images through an exponential equation, and the length of penetration of a superluminescent blue beam (λ=440 nm), through an inversely proportional function. Outcomes of this study are useful to monitor both research and industrial microalgae cultures.Possibility of understanding metabolic syndrome by probing dysregulation of metabolic and signaling network in bacteriahttps://peerj.com/preprints/277382019-05-162019-05-16Wenfa Ng
High fat diet and high glucose intake are commonly associated with incidence of metabolic syndrome that includes high cholesterol and diabetes. But how the two factors interplay in mediating diabetes remain poorly understood. While animal models could be used to probe the above hypothesized interplay between high fat diet and high glucose intake in mediating diabetes incidence, complex genetic background of the mammalian system seriously hamper the deciphering of the interconnection between phenotype and genes through analysis of functional genomic and epidemiological data. Furthermore, given the high conservation of central carbon metabolism across species between the three domains of life, what are analogs of the effects of high fat and high sugar diets in prokaryotic systems and what metabolic syndromes do they manifest? This work sought to trace the evolutionary ancestry of diabetes and high cholesterol syndrome as manifested in mammalian cells in prokaryotic systems. Using Escherichia coli as model organism, this work would heterologously express genes and pathways involved in mammalian fat metabolism in E. coli to help understand how a combined high fat and high glucose diet would interact in mediating prokaryotic version of diabetes and high cholesterol syndrome. Insights such as what are the genes differentially expressed during metabolization of high sugar and high fat diet by bacterial cells would hopefully inform the search for mammalian genes that predispose to metabolic syndrome by illuminating hitherto unknown genes and pathways implicated in the disease. But, what is perhaps more interesting from a fundamental perspective in this work is the search for suitable metabolic networks in which to study the prokaryotic version of diabetes and high cholesterol. Could it be overflow metabolism induced by high glucose uptake by E. coli? Or could activation of an enhanced lipid recycling pathway serve as a response to high fat infusion in bacteria? More importantly, could the manifested effects of high fat and high sugar diet be vertically inherited in bacteria similar to the incurable high cholesterol and diabetes in mammalian systems? Specifically, does manifestation of diabetes in bacteria results from epigenetic changes that mistune metabolic pathway and networks in an inheritable fashion? Finally, experiments with different types of substrates could be employed to examine the relative impact of high fat diet and high glucose intake on the extent in which central carbon metabolism in E. coli would be disturbed. Collectively, heterologous expression of mammalian genes involved in fat metabolism in E. coli opens a path to the exploration of prokaryotic version of high cholesterol and diabetes. But, what is perhaps more intriguing is tracing the evolutionary pathway that connects dysregulated sugar and fat metabolism in bacteria to their homologous clinical manifestations in mammalian systems.
High fat diet and high glucose intake are commonly associated with incidence of metabolic syndrome that includes high cholesterol and diabetes. But how the two factors interplay in mediating diabetes remain poorly understood. While animal models could be used to probe the above hypothesized interplay between high fat diet and high glucose intake in mediating diabetes incidence, complex genetic background of the mammalian system seriously hamper the deciphering of the interconnection between phenotype and genes through analysis of functional genomic and epidemiological data. Furthermore, given the high conservation of central carbon metabolism across species between the three domains of life, what are analogs of the effects of high fat and high sugar diets in prokaryotic systems and what metabolic syndromes do they manifest? This work sought to trace the evolutionary ancestry of diabetes and high cholesterol syndrome as manifested in mammalian cells in prokaryotic systems. Using Escherichia coli as model organism, this work would heterologously express genes and pathways involved in mammalian fat metabolism in E. coli to help understand how a combined high fat and high glucose diet would interact in mediating prokaryotic version of diabetes and high cholesterol syndrome. Insights such as what are the genes differentially expressed during metabolization of high sugar and high fat diet by bacterial cells would hopefully inform the search for mammalian genes that predispose to metabolic syndrome by illuminating hitherto unknown genes and pathways implicated in the disease. But, what is perhaps more interesting from a fundamental perspective in this work is the search for suitable metabolic networks in which to study the prokaryotic version of diabetes and high cholesterol. Could it be overflow metabolism induced by high glucose uptake by E. coli? Or could activation of an enhanced lipid recycling pathway serve as a response to high fat infusion in bacteria? More importantly, could the manifested effects of high fat and high sugar diet be vertically inherited in bacteria similar to the incurable high cholesterol and diabetes in mammalian systems? Specifically, does manifestation of diabetes in bacteria results from epigenetic changes that mistune metabolic pathway and networks in an inheritable fashion? Finally, experiments with different types of substrates could be employed to examine the relative impact of high fat diet and high glucose intake on the extent in which central carbon metabolism in E. coli would be disturbed. Collectively, heterologous expression of mammalian genes involved in fat metabolism in E. coli opens a path to the exploration of prokaryotic version of high cholesterol and diabetes. But, what is perhaps more intriguing is tracing the evolutionary pathway that connects dysregulated sugar and fat metabolism in bacteria to their homologous clinical manifestations in mammalian systems.Complexity of human walking: the attractor complexity index is sensitive to gait synchronization with visual and auditory cueshttps://peerj.com/preprints/277112019-05-072019-05-07Philippe Terrier
Background. During steady walking, gait parameters fluctuate from one stride to another with complex fractal patterns and long-range statistical persistence. When a metronome is used to pace the gait (sensorimotor synchronization), long-range persistence is replaced by stochastic oscillations (anti-persistence). Fractal patterns present in gait fluctuations are most often analyzed using detrended fluctuation analysis (DFA). This method requires the use of a discrete times series, such as intervals between consecutive heel strikes, as an input. Recently, a new nonlinear method, the attractor complexity index (ACI), has been shown to respond to complexity changes like DFA. But in contrast to DFA, ACI can be applied to continuous signals, such as body accelerations. The aim of this study was to further compare DFA and ACI in a treadmill experiment that induced complexity changes through sensorimotor synchronization. Methods. Thirty-six healthy adults walked 30 minutes on an instrumented treadmill under three conditions: no cueing, auditory cueing (metronome walking), and visual cueing (stepping stones). The center-of-pressure trajectory was discretized into time series of gait parameters, after which a complexity index (scaling exponent alpha) was computed via DFA. Continuous pressure position signals were used to compute the ACI. Correlations between ACI and DFA were then analyzed. The predictive ability of DFA and ACI to differentiate between cueing and no-cueing conditions was assessed using regularized logistic regressions and areas under the receiver operating characteristic curves (AUROC). Results. DFA and ACI were both significantly different among the cueing conditions. DFA and ACI were correlated (Pearson’s r = 0.78). Logistic regressions showed that DFA and ACI could differentiate between cueing/no cueing conditions with a high degree of confidence (AUROC = 1.0 and 0.96, respectively). Conclusion. Both DFA and ACI responded similarly to changes in cueing conditions and had comparable predictive power. This support the assumption that ACI could be used instead of DFA to assess the long-range complexity of continuous gait signals.
Background. During steady walking, gait parameters fluctuate from one stride to another with complex fractal patterns and long-range statistical persistence. When a metronome is used to pace the gait (sensorimotor synchronization), long-range persistence is replaced by stochastic oscillations (anti-persistence). Fractal patterns present in gait fluctuations are most often analyzed using detrended fluctuation analysis (DFA). This method requires the use of a discrete times series, such as intervals between consecutive heel strikes, as an input. Recently, a new nonlinear method, the attractor complexity index (ACI), has been shown to respond to complexity changes like DFA. But in contrast to DFA, ACI can be applied to continuous signals, such as body accelerations. The aim of this study was to further compare DFA and ACI in a treadmill experiment that induced complexity changes through sensorimotor synchronization. Methods. Thirty-six healthy adults walked 30 minutes on an instrumented treadmill under three conditions: no cueing, auditory cueing (metronome walking), and visual cueing (stepping stones). The center-of-pressure trajectory was discretized into time series of gait parameters, after which a complexity index (scaling exponent alpha) was computed via DFA. Continuous pressure position signals were used to compute the ACI. Correlations between ACI and DFA were then analyzed. The predictive ability of DFA and ACI to differentiate between cueing and no-cueing conditions was assessed using regularized logistic regressions and areas under the receiver operating characteristic curves (AUROC). Results. DFA and ACI were both significantly different among the cueing conditions. DFA and ACI were correlated (Pearson’s r = 0.78). Logistic regressions showed that DFA and ACI could differentiate between cueing/no cueing conditions with a high degree of confidence (AUROC = 1.0 and 0.96, respectively). Conclusion. Both DFA and ACI responded similarly to changes in cueing conditions and had comparable predictive power. This support the assumption that ACI could be used instead of DFA to assess the long-range complexity of continuous gait signals.Possible epigenetic influence on cellular differentiation and lineage segregation in Escherichia colihttps://peerj.com/preprints/277042019-05-062019-05-06Wenfa Ng
Epigenetics provides the critical connection between environmental influence and gene expression, where environmental stressors could modulate expression of specific genes in particular scenarios using molecular markers etched at the genome level. Hence, epigenetics likely play important roles in potentiating the development of specific lineages, cell fate or cellular differentiation. For example, when specific environmental stressor is present, epigenetic markers in the genome receive a signal for either activating or deactivating expression of particular sets of genes, which may be linked to the developmental trajectory of the organism. Using Escherichia coli as model organism, a possible study may investigate the role of epigenetics in influencing cellular differentiation of the bacterium. Specifically, a single E. coli cell would be propagated into a consortium of 12 or more bacterial cells in a microfluidics growth chamber. Genetic material extracted would be sent for single cell genomics, transcriptomics, and chromatin immunoprecipitation sequencing (ChIP-seq). After profiling, the residual population would be diverted by microchannels to 6 different cell growth chambers, where they would be cultivated under identical conditions for understanding possible triggers to cell differentiation. At suitable time points of 2, 4, 6, 8, 10, 12 hours, single cell would be extracted from each growth chamber for profiling single cell genomics, transcriptomics, and epigenetics markers. Optical and confocal laser scanning microscopy would provide readout of cell morphologies. Comparison of the readout between the original clonal population and those of the different growth chambers may provide important points for correlating epigenetic markers with gene expression and phenotypic readout in cell lineage, fate and differentiation. In subsequent experiments, different environmental stressors such as pH, imbalance nutrient composition between carbon and nitrogen, nanoparticles or heavy metals, could be used as triggers for specific cell growth response guided by epigenetic programmes embedded within the epigenome of the bacterium. Collectively, epigenetics hold influence for cellular differentiation in view of specific environmental stressors, where epigenetic markers on the genome communicate specific environmental factor's effect on the organism through altering expression of particular sets of genes, that result in different cell fate, lineage and differentiation. Using modern single cell techniques at the genomics, transcriptomics and epigenomics level, the study hopes to elucidate epigenetic potentiators of cellular differentiation in E. coli with and without environmental stressors such as nutrient deprivation, pH and toxic metals.
Epigenetics provides the critical connection between environmental influence and gene expression, where environmental stressors could modulate expression of specific genes in particular scenarios using molecular markers etched at the genome level. Hence, epigenetics likely play important roles in potentiating the development of specific lineages, cell fate or cellular differentiation. For example, when specific environmental stressor is present, epigenetic markers in the genome receive a signal for either activating or deactivating expression of particular sets of genes, which may be linked to the developmental trajectory of the organism. Using Escherichia coli as model organism, a possible study may investigate the role of epigenetics in influencing cellular differentiation of the bacterium. Specifically, a single E. coli cell would be propagated into a consortium of 12 or more bacterial cells in a microfluidics growth chamber. Genetic material extracted would be sent for single cell genomics, transcriptomics, and chromatin immunoprecipitation sequencing (ChIP-seq). After profiling, the residual population would be diverted by microchannels to 6 different cell growth chambers, where they would be cultivated under identical conditions for understanding possible triggers to cell differentiation. At suitable time points of 2, 4, 6, 8, 10, 12 hours, single cell would be extracted from each growth chamber for profiling single cell genomics, transcriptomics, and epigenetics markers. Optical and confocal laser scanning microscopy would provide readout of cell morphologies. Comparison of the readout between the original clonal population and those of the different growth chambers may provide important points for correlating epigenetic markers with gene expression and phenotypic readout in cell lineage, fate and differentiation. In subsequent experiments, different environmental stressors such as pH, imbalance nutrient composition between carbon and nitrogen, nanoparticles or heavy metals, could be used as triggers for specific cell growth response guided by epigenetic programmes embedded within the epigenome of the bacterium. Collectively, epigenetics hold influence for cellular differentiation in view of specific environmental stressors, where epigenetic markers on the genome communicate specific environmental factor's effect on the organism through altering expression of particular sets of genes, that result in different cell fate, lineage and differentiation. Using modern single cell techniques at the genomics, transcriptomics and epigenomics level, the study hopes to elucidate epigenetic potentiators of cellular differentiation in E. coli with and without environmental stressors such as nutrient deprivation, pH and toxic metals.Merits of constant expression of CRISPR loci in adaptive immunity of bacteriahttps://peerj.com/preprints/276912019-04-292019-04-29Wenfa Ng
Bacteria fend off attack of bacteriophage through a variety of systems such as restriction-modification as well as clustered regularly interspersed short palindromic repeats (CRISPR). CRISPR is an adaptive immune system that provides a molecular memory of past attacks of bacteriophages on the bacterial strain in a vertically inheritable fashion. More importantly, such molecular memory of past phage infection is utilized in guiding a precision attack on the nucleic acids of invading bacteriophages. To do this, snippets of DNA from invading phages that have been neutralized are inserted into CRISPR-loci in the bacterial genome. Transcription of the CRISPR loci provides active RNA variants of the DNA snippets from phages useful for guiding the Cas9 endonuclease to invading phage DNA through complementary base pairing defined by a spacer region. While the system provides real-time surveillance of the bacterial cytoplasm for phage DNA resembling those from past infections, energetic cost of constantly transcribing the CRISPR loci might be high. Specifically, as currently understood, the CRISPR system would express phage DNA snippets catalogued in the CRISPR loci irrespective of environmental and nutritional conditions to help fend off possible infections by the same phages. However, phages responsible for past infections may not be present in the vicinity of the bacterial cell’s environment, which meant that expression of the CRISPR loci might be a waste of cellular energy and resources without any gain in fitness advantage to the bacterial cell compared to those from another species in the same environment. Hence, the evolutionary forces that shape the retention of the extant form of CRISPR remains to be understood in the context of how cellular energetics of adaptive immunity connects with bacterial fitness. Theoretically, a better system would involve the selective expression of specific CRISPR loci targeting the DNA or RNA of particular bacteriophage invading the cell. Such a system would incur less energy and resources to maintain, but would require another layer of intracellular surveillance able to identify the type and species of invading bacteriophage. Doing so would return us to the same problem as a molecular surveillance system requires key elements of recognition and actuation where recognition requires a molecular template of sequence information characteristic of particular bacteriophage. Given that DNA is a more stable format for storing sequence information compared to RNA, and that complementary base pairing as recognition mechanism require single stranded nucleic acid, current incarnation of CRISPR loci might be close to optimal in device architecture and functional logic. Hence, could we do better in redesigning bacterial adaptive immune system able to recognize a diversity of phages involved in past infection of a species or strain at reduced energetic and material cost?
Bacteria fend off attack of bacteriophage through a variety of systems such as restriction-modification as well as clustered regularly interspersed short palindromic repeats (CRISPR). CRISPR is an adaptive immune system that provides a molecular memory of past attacks of bacteriophages on the bacterial strain in a vertically inheritable fashion. More importantly, such molecular memory of past phage infection is utilized in guiding a precision attack on the nucleic acids of invading bacteriophages. To do this, snippets of DNA from invading phages that have been neutralized are inserted into CRISPR-loci in the bacterial genome. Transcription of the CRISPR loci provides active RNA variants of the DNA snippets from phages useful for guiding the Cas9 endonuclease to invading phage DNA through complementary base pairing defined by a spacer region. While the system provides real-time surveillance of the bacterial cytoplasm for phage DNA resembling those from past infections, energetic cost of constantly transcribing the CRISPR loci might be high. Specifically, as currently understood, the CRISPR system would express phage DNA snippets catalogued in the CRISPR loci irrespective of environmental and nutritional conditions to help fend off possible infections by the same phages. However, phages responsible for past infections may not be present in the vicinity of the bacterial cell’s environment, which meant that expression of the CRISPR loci might be a waste of cellular energy and resources without any gain in fitness advantage to the bacterial cell compared to those from another species in the same environment. Hence, the evolutionary forces that shape the retention of the extant form of CRISPR remains to be understood in the context of how cellular energetics of adaptive immunity connects with bacterial fitness. Theoretically, a better system would involve the selective expression of specific CRISPR loci targeting the DNA or RNA of particular bacteriophage invading the cell. Such a system would incur less energy and resources to maintain, but would require another layer of intracellular surveillance able to identify the type and species of invading bacteriophage. Doing so would return us to the same problem as a molecular surveillance system requires key elements of recognition and actuation where recognition requires a molecular template of sequence information characteristic of particular bacteriophage. Given that DNA is a more stable format for storing sequence information compared to RNA, and that complementary base pairing as recognition mechanism require single stranded nucleic acid, current incarnation of CRISPR loci might be close to optimal in device architecture and functional logic. Hence, could we do better in redesigning bacterial adaptive immune system able to recognize a diversity of phages involved in past infection of a species or strain at reduced energetic and material cost?Search for receptors in immune cells that bind cancer cell antigens and their activation in silent caseshttps://peerj.com/preprints/276702019-04-202019-04-20Wenfa Ng
The immune checkpoint plays an important role in keeping immune cells in check for protecting tissues and organs from attack by the body’s own immune system. Similar concepts also apply in how cancer cells managed to fool immune cells through the surface display of particular antigens that mimic those exhibited by normal body cells. Specifically, cancer cells display antigens that bind to receptors on immune cells that subsequently prevent an attack on the cancer cells. Such binding between cancer antigens and immune cell receptors can be prevented through the use of checkpoint inhibitors antibodies specific for particular receptors on immune cells; thereby, unleashing immune cells to mount an immune response against cancer cells. While demonstrating good remissions in many patients where tumours shrunk substantially after administration of checkpoint inhibitors, cases exist where an overactivated immune system cause harm to organs and tissues culminating in multiple organ failure. Analysis of such toxicity effects of checkpoint inhibitors revealed that generic nature of targeted immune receptor plays a pivotal role in determining extent of side effects. Specifically, if the target immune receptor participates in checkpoints that prevent immune cells from attacking host cells, unleashing such receptors in cancer therapy may have untoward effects on patient’s health. Hence, the goal should be the selection of immune cell receptor specific to cancer cell antigens and which does not bind antigens or ligands displayed by the body’s cells. Such receptors would provide ideal targets for the development of checkpoint inhibitor antibodies for unleashing immune cells against cancer cells. To search for non-generic receptors that bind cancer cell antigens only, a combined computational and experimental approach could be used where ensemble of surface antigens on cancer cells and available receptors on immune cells could be profiled by biochemical assays. Downstream purification of ligands and receptors would provide for both structural elucidation and amino acid sequencing useful for bioinformatic search of homologous sequences. Knowledge of the antigens’ and receptors’ structures and amino acid sequence would subsequently serve as inputs to computational algorithms that models molecular docking events between receptor and antigen. This paves the way for heterologous expression of putative ligand and receptor in cell lines cultured in co-culture format for assessing binding between ligand and receptor, and more importantly, its physiological effects. Ability of immune receptor to bind to ligands on normal cells could also be assessed. Similar co-culture studies could be conducted with cancer cells and different immune cell types to check for reproducibility of observed effect in cell lines. Finally, antibodies could be raised for candidate receptors whose inhibition would not result in systemic attack of immune cells on host cells.
The immune checkpoint plays an important role in keeping immune cells in check for protecting tissues and organs from attack by the body’s own immune system. Similar concepts also apply in how cancer cells managed to fool immune cells through the surface display of particular antigens that mimic those exhibited by normal body cells. Specifically, cancer cells display antigens that bind to receptors on immune cells that subsequently prevent an attack on the cancer cells. Such binding between cancer antigens and immune cell receptors can be prevented through the use of checkpoint inhibitors antibodies specific for particular receptors on immune cells; thereby, unleashing immune cells to mount an immune response against cancer cells. While demonstrating good remissions in many patients where tumours shrunk substantially after administration of checkpoint inhibitors, cases exist where an overactivated immune system cause harm to organs and tissues culminating in multiple organ failure. Analysis of such toxicity effects of checkpoint inhibitors revealed that generic nature of targeted immune receptor plays a pivotal role in determining extent of side effects. Specifically, if the target immune receptor participates in checkpoints that prevent immune cells from attacking host cells, unleashing such receptors in cancer therapy may have untoward effects on patient’s health. Hence, the goal should be the selection of immune cell receptor specific to cancer cell antigens and which does not bind antigens or ligands displayed by the body’s cells. Such receptors would provide ideal targets for the development of checkpoint inhibitor antibodies for unleashing immune cells against cancer cells. To search for non-generic receptors that bind cancer cell antigens only, a combined computational and experimental approach could be used where ensemble of surface antigens on cancer cells and available receptors on immune cells could be profiled by biochemical assays. Downstream purification of ligands and receptors would provide for both structural elucidation and amino acid sequencing useful for bioinformatic search of homologous sequences. Knowledge of the antigens’ and receptors’ structures and amino acid sequence would subsequently serve as inputs to computational algorithms that models molecular docking events between receptor and antigen. This paves the way for heterologous expression of putative ligand and receptor in cell lines cultured in co-culture format for assessing binding between ligand and receptor, and more importantly, its physiological effects. Ability of immune receptor to bind to ligands on normal cells could also be assessed. Similar co-culture studies could be conducted with cancer cells and different immune cell types to check for reproducibility of observed effect in cell lines. Finally, antibodies could be raised for candidate receptors whose inhibition would not result in systemic attack of immune cells on host cells.