What is engineered probiotics? Engineered probiotics are microorganisms with optimized metabolic processes, typically achieved using synthetic biology and omics technologies.
In recent years, genome sequencing has become more affordable and some of the tools for editing and modifying microbial genomes have become more powerful, enable us to engineer probiotics according to our own ideas.
By means of gene editing, probiotics can have a variety of beneficial properties, and can treat specific diseases, which is beneficial to human health. Engineered probiotics is a promising research which may become new methods to solve some problems.
Scientists have also developed engineered microorganisms that are relevant to industrial applications. Microbe bioengineering has the potential to improve the nutritional value and health benefits of food products. However, the application of engineered probiotics still faces a series of challenges.
According to knowledge of the gut microbiota, the phylogenetic range and characteristics of the
organisms are under investigation as novel therapeutics. (Next-generation probiotics)
As the microbiota studies proceed, single bacterial strains are screened and isolated, aiming to characterize their relationship with the amelioration of specific diseases.
Among these, some of them are expected to emerge as next generation probiotics. Next-generation probiotics are live microorganisms identified based on comparative microbiota analyses that, when administered in adequate amounts, confer a specific health benefit on the host.
Traditional probiotics such as Bifidobacterium spp., Lactobacillus spp. and many others may effect on amelioration of diseases however, their effects are statistically marginal.
On the other hand, the administration of traditional probiotics does not aim against specific diseases. Based on these situations, identification and characterization of novel and disease-specific next-generation probiotics are urgently needed.
Metagenomics studies the genetic material of uncultured microorganisms (bacteria, virus and archaea). These microorganisms are obtained directly from biological samples, including human, animal, plant and environmental samples even food products. Although metagenomics is a new research field, we have seen the rapid growth of computational methods and the publication of numerous articles in this field in recent years. One of the main goals of metagenomics is to determine the role of these microorganisms. Recently, new sequencing technologies and significant reduction in sequencing costs have greatly contributed to the development of this approach. One of the main applications of metagenomics is in the field of health and disease. Today, using this science, the origin of many common human diseases, including gastrointestinal and metabolic diseases, has been identified. Scientists have also used this knowledge to develop microbial-based therapies, such as using the food product fortified with beneficial microbes.
Different stages of a metagenomics study:
A) Sampling from habitat
B) Filtering particles, typically by size
C) DNA extraction and analysis
D) Cloning and library
E) Sequencing of clones
F) Delete low quality sequences
۱) Saving files in FASTQ format
۲) Performing bioinformatics analyzes and determining the abundance and diversity of the microbial community.
Metabolomics is the assessment of all the low-molecular-weight molecules called metabolites (with a molecular mass <1,500 Da in any organism (from fish to humans)) by advanced analytical chemistry techniques in a cell, tissue, organ, organism or biofluid. This approach is relatively new and more comprehensive, cheaper and faster than clinical chemistry. This field of life science in conjunction with statistical methods, examines the metabolome and used in a wide range of research, including animal health studies, biomedical research, food and nutritional analysis and drug testing.
The metabolome is a set of all the low-molecular-weight metabolites that can demonstrate biological disorders in the host. Perturbations in metabolic pathways in an organism, causes these disorders. Metabolites are the end products of genes, proteins, and enzymes and are specific to each cell or tissue. These small molecules provide the chemical fuel for cellular processes, are essential to life and cellular signaling pathways. Metabolites can be primary, such as lipids, amino acids, nucleic acids, sugars, short peptides, or organic acids that are endogenous, their synthesis is encoded by the host genome and are highly conserved, or can be secondary, such as plant/food phytochemicals, food additives, microbial products, chemical contaminants, and pesticides that are exogenous, highly variable and depend on environmental exposures, dietary patterns and gut microflora. Primary metabolites are essential for growth and physiological functions. Deficiency of essential metabolites leads to various types of diseases such as pellagra (lack of vitamin B3), rickets (lack of vitamin D), kwashiorkor (lack of protein or essential amino acids), and scurvy (lack of vitamin C). Each person’s metabolome is unique and depends on various factors such as genetics, age, gender, geographical location, diet and environmental factors.
Methods of measuring metabolites
The metabolome is complex and large, and its evaluation requires more advanced tools and equipment than the genome and proteome. The various techniques used to measure metabolites include the following:
Integrated ion mobility spectrometry-mass spectrometry (IMS-MS)
Gas chromatography-mass spectrometry (GC-MS)
LC-MS/NMR
Samples used to measure metabolites are a cell culture, an organ, a tissue biopsy or biofluid such as urine, blood, cerebrospinal fluid (CSF), sweat and saliva.
Today, there are well-equipped laboratories in this field with a complete set of accurate analytical tools, various types of databases and software to measure metabolites globally.
Metabolomics and diseases
The primary use of metabolomics has been to diagnosis of diseases and identifying pathological conditions. Metabolic diseases fall into 13 general categories, which are diseases related to:
Carbohydrate metabolism
Amino acid metabolism
Organic acid metabolism
Fatty acid oxidation
Nucleotide metabolism
Porphyrin metabolism
Urea cycle metabolism
Steroid metabolism
Mitochondrial function
Peroxisomal function
Lipid metabolism
Metal storage
Lysosomal storage
Hundreds to thousands of metabolites can be measured simultaneously using metabolomic techniques. For this reason, the most widely used of these techniques is for newborn screening and the detection of inborn errors of metabolism (IEMs) such as alkoptunuria, phenylketonuria or PKU, Lesch-Nyhan syndrome and Gaucher’s disease. Metabolomics is also used in personalized medicine for diagnosis and the follow-up treatment of metabolomic diseases such as autoimmune diseases, diabetes mellitus, atherosclerosis, hypertension, hypothyroidism, chronic inflammation, chronic kidney disease (CKD), canser, allergies, inflammatory bowel disease (IBD), obesity, metabolic syndrome, Tay-Sachs and albinism.
Prepared by: Parvin Zarei
References
Challenges and Opportunitiesof Metabolomics
Metabolomics for Investigating Physiological and Pathophysiological Processes
This approach is used to identify the qualitative and quantitative RNA levels in the whole genome. This includes which transcripts are present and the levels of their expression. Although only 2% of the DNA is translated in to protein, almost 80% of the genome is transcribed. This includes the coding RNA, short RNA, including microRNA, piwi RNA, small nuclear RNA. Apart from acting as an intermediate between DNA and protein, RNA also has structural and regulatory functions during native and altered states. They have been shown to have a role in myocardial infarction, adipose differentiation, diabetes, endocrine regulation, neuron development, and others. Thus, it is crucial to understand which transcripts are expressed at a time. Apart from next generation sequencing, probe-based assays, and RNA-seq are also used in this approach.
What is Transcriptomics used for?
Transcriptomics allows identification of genes and pathways that respond to and counteract biotic and abiotic environmental stresses. The non-targeted nature of transcriptomics allows the identification of novel transcriptional networks in complex systems. Transcriptome databases have grown and increased in utility as more transcriptomes are collected and shared by researchers. Measuring the expression of an organism’s genes in different tissues or conditions, or at different times, gives information on how genes are regulated and reveals details of an organism’s biology. It can also be used to infer the functions of previously unannotated genes. Transcriptome analysis has enabled the study of how gene expression changes in different organisms and has been instrumental in the understanding of human disease. An analysis of gene expression in its entirety allows detection of broad coordinated trends which cannot be discerned by more targeted assays.
Techniques
There are two key contemporary techniques in the field: microarrays, which quantify a set of predetermined sequences, and RNA-Seq, which uses high-throughput sequencing to record all transcripts. As the technology improved, the volume of data produced by each transcriptome experiment increased. As a result, data analysis methods have steadily been adapted to more accurately and efficiently analyze increasingly large volumes of data.
Proteomics is the large-scale study of proteins. The proteome is the entire set of proteins produced or modified by an organism or system. Proteomics enables the identification of ever-increasing numbers of proteins. This varies with time and distinct requirements, or stresses, that a cell or organism undergoes. This field is involved in identifying protein levels, modifications, and interactions at the level of genome. Proteomics is an interdisciplinary domain that has benefitted greatly from the genetic information of various genome projects, including the Human Genome Project Protein-protein interactions can be studied through phage display, classical yeast two hybrid, affinity purification, and ChiP-Seq. The majority of proteins are regulated through post-translational modifications, such as phosphorylation, acetylation, ubiquitination, nitrosylation, and glycosylation. These modifications are involved in maintaining cellular structure and function. Mass spectroscopy based techniques are being used to analyze the global proteomic changes and quantifying the post translational modifications. Proteomics generally refers to the large-scale experimental analysis of proteins and proteomes, but often refers specifically to protein purification and mass spectrometry.
Techniques
Antibody-based methods. Techniques such as ELISA (enzyme-linked immunosorbent assay) and western blotting rely on the availability of antibodies targeted toward specific proteins or epitopes to identify proteins and quantify their expression levels.
Gel-based methods.
Chromatography-based methods.
Mass spectrometry with LC–MS-MS and MALDI-TOF/TOF being widely used equipment is the central among current proteomics. However, utilization of proteomics facilities including the software for equipment, databases and the requirement of skilled personnel substantially increase the costs, therefore limit their wider use especially in the developing world.
applications
Proteomics-based technologies are utilized in various capacities for different research settings such as detection of various diagnostic markers, candidates for vaccine production, understanding pathogenicity mechanisms, alteration of expression patterns in response to different signals and interpretation of functional protein pathways in different diseases. Proteomics is practically intricate because it includes the analysis and categorization of overall protein signatures of a genome. Furthermore, the proteome is highly dynamic because of complex regulatory systems that control the expression levels of proteins. Proteomics is crucial for early disease diagnosis, prognosis and to monitor the disease development. Furthermore, it also has a vital role in drug development as target molecules. Proteomics is one of the most significant methodology to comprehend the gene function although, it is much more complex compared with genomic.
Epigenomics is the study of the complete set of epigenetic modifications on the genetic material of a cell, known as the epigenome. The field is analogous to genomics and proteomics, which are the study of the genome and proteome of a cell. Plant flavones are said to be inhibiting epigenomic marks that cause cancers. Indeed, Epigenomics refers to identifying modifications of DNA or DNA-associated proteins. These include DNA and methylation. Cell fate and functions can be modified by modifications in DNA and histones, apart from genetic changes. These changes can be based on the environment and are passed onto progeny. Epigenetic changes in genome can also act as markers for metabolic syndromes, cardiovascular diseases, and physiological disorders. These changes can be cell-and tissue-specific. Thus, it is critical to identify the epigenetic changes during native and diseased states. Next generation sequencing is also used to assess DNA modifications.
What is the difference between epigenetics and epigenomics?
Epigenetics focuses on processes that regulate how and when certain genes are turned on and turned off, while epigenomics pertains to analysis of epigenetic changes across many genes in a cell or entire organism.
What is Epigenomic profiling?
Epigenomics involves the profiling and analysis of epigenetic marks across the genome. These processes modify local genome activity without changing the underlying DNA sequences and thus determine cellular phenotypes by regulating gene expression dynamics.
What technology is essential for Epigenomics?
Epigenomics has only become possible in recent years because of the advent of various sequencing tools and technologies, such as DNA microarrays, cheap whole-genome resequencing, and databases for studying entire genomes.
Multiomics is a new approach where the data sets of different omic groups are combined during analysis. The different omic strategies employed during multiomics are genome, proteome, transcriptome, epigenome, and microbiome. Multiomics, multi-omics, integrative omics, “panomics” or ‘pan-omics’ is a biological analysis approach in which the data sets are multiple above omics. In other words, the use of multiple omics technologies to study life in a concerted way. By combining these “omes”, scientists can analyze complex biological big data to find novel associations between biological entities, pinpoint relevant biomarkers and build elaborate markers of disease and physiology. In doing so, multiomics integrates diverse omics data to find a coherently matching geno-pheno-envirotype relationship or association.
Multiomics strategy
With the progress in all the different omics fields, it is being increasingly recognized that the answer to a research question cannot be answered by one form of omics. The microbiome influences the gene and protein expression which in turn influence the metabolome, and all these processes crosstalk and regulate each other. Studying these processes in their entirety is critical to find strategies to treat diseases. This is where the multiomics field is coming in. This field encompasses all the omics fields and trues to understand the native and altered state of an organism by the analysis of the data from different omics experiments.
Multiomics analysis
Methods for parallel single-cell genomic and transcriptomic analysis can be based on simultaneous amplification or physical separation of RNA and genomic DNA. Modern sequencing technology has led to many comprehensive assays being routinely available to experimenters, giving us different ways to peek at the internal doings of the cells, each experiment revealing a different part of some underlying processes. If we treat the DNA with bisulfite prior to sequencing, cytosine residues are converted to uracil, but 5-methylcytosine residues are unaffected. This allows us to probe the methylation patterns of the genome, or its methylome. By sequencing the mRNA molecules in a cell, we can calculate the abundance, in different samples, of different mRNA transcripts, or uncover its transcriptome. Performing different experiments on the same samples, for instance RNA-seq, DNA-seq, and BS-seq, results in multi-dimensional omics datasets, which enable the study of relationships between different biological processes, e.g. DNA methylation, mutations, and gene expression, and the leveraging of multiple data types to draw inferences about biological systems.
Paraprobiotics or immobilized probiotics, are kind of postbiotics which when ingested, may have the ability to exert positive biological responses and restore intestinal homeostasis in a similar manner to probiotics. Paraprobiotics are currently being referred to as modified, inactivated, non-viable, para- or ghost probiotics. Paraprobiotics, the immobilized version of probiotics are gaining traction in recent years due to the concerns about the possibility of low tolerance of probiotics, especially in pediatric populations and in severely ill or immunocompromised patients. Paraprobiotics seem to have similar beneficial properties as live probiotics with fewer of the constraints associated with unstable, diminishing bacteria.
Production of paraprobiotics
Paraprobiotics could be generated using different methods including: Heat-inactivation, Ultraviolet-inactivation, Chemical treatment (e.g. formalin), Gamma-irradiation, and Sonication. In most cases, heat treatment is considered the method of choice for deactivating probiotic strains. The effect that different types of inactivation have on bacterial structure and components as well as the maintenance of probiotic properties requires further research.
Mechanism of action
The mechanisms of action for paraprobiotics is less understood, though the possible mechanisms include immune system regulation and interference with pathogen attachment to host cells. Limited research hypothesizes that immobilized paraprobiotics release key bacterial components, such as lipoteichoic acids, peptidoglycans, or exopolysaccharides which exhibit key immunomodulation effects and antagonizing properties against pathogens.
General paraprobiotics applications
Emerging clinical and pre-clinical studies have demonstrated that paraprobiotics play a role in general health and well-being and for improving host immune function like that of probiotics. It is proved that paraprobiotics induce changes in the gut microbiome and the altered gut microbial composition is associated with increased levels of innate and acquired immunity biomarkers. Paraprobiotics also seem to exhibit antioxidant effects and has indicated its potential applications in food and pharmaceutical industries.
Paraprobiotics applications in clinical treatment
Paraprobiotics (mostly heat-killed) seem to be beneficial for the following clinical applications:
Whole genome sequencing (WGS) is the most global approach to identifying genetic variations. Whole genome sequencing or full genome sequencing, is the process of determining the entirety of the DNA sequence of an organism’s genome at a single time. Genomic information has been instrumental in identifying inherited disorders, characterizing the mutations that drive cancer progression, and tracking disease outbreaks. This entails sequencing all of an organism’s chromosomal DNA as well as DNA contained in the mitochondria and, for plants, in the chloroplast. Whole genome sequencing has largely been used as a research. In the future of personalized medicine, whole genome sequence data may be an important tool to guide therapeutic intervention.
Advantages of Whole-Genome Sequencing
Provides a high-resolution, base-by-base view of the genome
Captures both large and small variants that might be missed with targeted approaches
Identifies potential causative variants for further follow-up studies of gene expression and regulation mechanisms
Delivers large volumes of data in a short amount of time to support assembly of novel genomes
Next generation sequencing
The feasibility of WGS analysis is under the support of next generation sequencing (NGS) technologies, which require substantial computational and biomedical resources to acquire and analyze large and complex sequence data. Meanwhile, the rapid progress and innovation of NGS technology has successfully enabled the generation of large volumes of sequence data and reduced the expense for WGS. While WGS method is commonly associated with sequencing human genomes, the scalable, flexible nature of next-generation sequencing (NGS) technology makes it equally useful for sequencing any species, such as agriculturally important livestock, plants, or disease-related microbes.
