Evaluation of CRISPR Diversity in the Human Skin Microbiome for Personal Identification

NeoGenesis MB-1 with CRISPR Technology Reduces the Effects of the Viruses (Phages) Associated with Acne - Case Report

We present a case of acne successfully treated with a topical spray containing live bacteria. The live bacteria used in the spray contain CRISPR, and adaptive immune system in the bacteria that are used to disable viral replication. Because acne skin contains bacteria in the microbiome where a shift toward non-CRISPR bacteria occurs, these bacteria are susceptible to bacteriophage infection and lysogeny. Normalizing the bacterial microbiome to one containing more CRISPR-containing bacteria renormalizes the microbiome by killing inflammation-causing bacteriophage infecting the non-CRISPR bacteria associated with acne.

Explore variation of salivary bacteria across time and geolocations

Saliva is an informative body fluid that can be found at various crime scenes, and the salivary bacterial community has been revealed it is a potential auxiliary target for forensic identification. However, the variation of salivary bacterial community composition across time and geolocation needs to be explored. The study was designed to be carried out during the winter vacation that was across about 50 days and eight geographic locations. The high throughput sequencing was performed with the V3-V4 region of the16S rRNA gene to explore salivary bacterial community composition. An overall slight fluctuation of the salivary bacteria was observed, which primarily occurred in the relative abundance of the salivary bacterial taxa. The results of principal coordinate analysis and hierarchical clustering showed samples were clustered by the individuals. All individuals could be correctly identified with the random forest model. In summation, although the relative abundance of salivary bacteria varied across the changes of time and geolocation, the individualized characteristic of salivary bacteria remained steady, which is beneficial for the salivary bacterial application in personal identification.

Metatranscriptomic characterization of six types of forensic samples and its potential application to body fluid/tissue identification: A pilot study

Microorganisms are potential markers for identifying body fluids (venous and menstrual blood, semen, saliva, and vaginal secretion) and skin tissue in forensic genetics. Existing published studies have mainly focused on investigating microbial DNA by 16 S rRNA gene sequencing or metagenome shotgun sequencing. We rarely find microbial RNA level investigations on common forensic body fluid/tissue. Therefore, the use of metatranscriptomics to characterize common forensic body fluids/tissue has not been explored in detail, and the potential application of metatranscriptomics in forensic science remains unknown. Here, we performed 30 metatranscriptome analyses on six types of common forensic sample from healthy volunteers by massively parallel sequencing. After quality control and host RNA filtering, a total of 345,300 unigenes were assembled from clean reads. Four kingdoms, 137 phyla, 267 classes, 488 orders, 985 families, 2052 genera, and 4690 species were annotated across all samples. Alpha- and beta-diversity and differential analysis were also performed. As a result, the saliva and skin groups demonstrated high alpha diversity (Simpson index), while the venous blood group exhibited the lowest diversity despite a high Chao1 index. Specifically, we discussed potential microorganism contamination and the "core microbiome," which may be of special interest to forensic researchers. In addition, we implemented and evaluated artificial neural network (ANN), random forest (RF), and support vector machine (SVM) models for forensic body fluid/tissue identification (BFID) using genus- and species-level metatranscriptome profiles. The ANN and RF prediction models discriminated six forensic body fluids/tissue, demonstrating that the microbial RNA-based method could be applied to BFID. Unlike metagenomic research, metatranscriptomic analysis can provide information about active microbial communities; thus, it may have greater potential to become a powerful tool in forensic science for microbial-based individual identification. This study represents the first attempt to explore the application potential of metatranscriptome profiles in forensic science. Our findings help deepen our understanding of the microorganism community structure at the RNA level and are beneficial for other forensic applications of metatranscriptomics.

Potential application of Staphylococcus species detection in the specific identification of saliva

When found at crime scenes, saliva constitutes forensically relevant evidence. Although several tests have been developed to effectively identify saliva in such circumstances, most cannot discriminate between saliva and nasal secretion. Recently, studies have developed saliva tests involving oral bacteria as salivary markers. Although the specificity of such tests has been evaluated on most biological specimens, their specificity for nasal secretion samples remains to be tested. Herein, to improve the specificity of the saliva detection tests for nasal secretion samples, we reanalyzed a public microbiome dataset and conducted inhouse 16S rRNA sequencing to identify a new marker to distinguish between saliva and nasal secretions. The sequencing data indicated the existence of oral bacteria such as Streptococcus in nasal secretion samples, which may be responsible for the false positives in the saliva tests. Furthermore, we found that including the 16S rRNA gene of the genus Staphylococcus as a nasal secretion marker may improve the specificity of PCR-based saliva tests for nasal secretion samples. In addition, we assessed the specificity of previously developed salivary bacteria detection tests for nasal secretion samples and oral bacterial markers were detected in two of eight nasal secretion samples, which led to the false positive results for saliva detection. Thus, the specificity of such tests can be improved by adding Staphylococcus as a nasal marker, as revealed by our sequencing analysis.

Identification and characterization of two CRISPR/Cas systems associated with the mosquito microbiome

The microbiome profoundly influences many traits in medically relevant vectors such as mosquitoes, and a greater functional understanding of host-microbe interactions may be exploited for novel microbial-based approaches to control mosquito-borne disease. Here, we characterized two novel clustered regularly interspaced short palindromic repeats (CRISPR)/Cas systems in Serratia sp. Ag1, which was isolated from the gut of an Anopheles gambiae mosquito. Two distinct CRISPR/Cas systems were identified in Serratia Ag1, CRISPR1 and CRISPR2. Based on cas gene composition, CRISPR1 is classified as a type I-E CRISPR/Cas system and has a single array, CRISPR1. CRISPR2 is a type I-F system with two arrays, CRISPR2.1 and CRISPR2.2. RT-PCR analyses show that all cas genes from both systems are expressed during logarithmic growth in culture media. The direct repeat sequences of CRISPRs 2.1 and 2.2 are identical and found in the arrays of other Serratia spp., including S. marcescens and S. fonticola , whereas CRISPR1 is not. We searched for potential spacer targets and revealed an interesting difference between the two systems: only 9 % of CRISPR1 (type I-E) targets are in phage sequences and 91 % are in plasmid sequences. Conversely, ~66 % of CRISPR2 (type I-F) targets are found within phage genomes. Our results highlight the presence of CRISPR loci in gut-associated bacteria of mosquitoes and indicate interplay between symbionts and invasive mobile genetic elements over evolutionary time.

Analysis of genetic structure and function of clustered regularly interspaced short palindromic repeats loci in 110 Enterococcus strains

Clustered regularly interspaced short palindromic repeats (CRISPR) and their CRISPR-associated proteins (Cas) are an adaptive immune system involved in specific defenses against the invasion of foreign mobile genetic elements, such as plasmids and phages. This study aims to analyze the gene structure and to explore the function of the CRISPR system in the Enterococcus genome, especially with regard to drug resistance. The whole genome information of 110 enterococci was downloaded from the NCBI database to analyze the distribution and the structure of the CRISPR-Cas system including the Cas gene, repeat sequences, and spacer sequence of the CRISPR-Cas system by bioinformatics methods, and to find drug resistance-related genes and analyze the relationship between them and the CRISPR-Cas system. Multilocus sequence typing (MLST) of enterococci was performed against the reference MLST database. Information on the drug resistance of Enterococcus was retrieved from the CARD database, and its relationship to the presence or absence of CRISPR was statistically analyzed. Among the 110 Enterococcus strains, 39 strains (35.45%) contained a complete CRISPR-Cas system, 87 CRISPR arrays were identified, and 62 strains contained Cas gene clusters. The CRISPR system in the Enterococcus genome was mainly type II-A (59.68%), followed by type II-C (33.87%). The phylogenetic analysis of the cas1 gene sequence was basically consistent with the typing of the CRISPR-Cas system. Of the 74 strains included in the study for MLST typing, only 19 (25.68%) were related to CRISPR-Cas typing, while the majority of the strains (74.32%) of MLST typing were associated with the untyped CRISPR system. Additionally, the CRISPR-Cas system may only be related to the carrying rate of some drug-resistant genes and the drug-resistant phenotype. In conclusion, the distribution of the enterococcus CRISPR-Cas system varies greatly among different species and the presence of CRISPR loci reduces the horizontal transfer of some drug resistance genes.

Towards standardized and reproducible research in skin microbiomes

Skin is a complex organ serving a critical role as a barrier and mediator of interactions between the human body and its environment. Recent studies have uncovered how resident microbial communities play a significant role in maintaining the normal healthy function of the skin and the immune system. In turn, numerous host-associated and environmental factors influence these communities' composition and diversity across the cutaneous surface. In addition, specific compositional changes in skin microbiota have also been connected to the development of several chronic diseases. The current era of microbiome research is characterized by its reliance on large data sets of nucleotide sequences produced with high-throughput sequencing of sample-extracted DNA. These approaches have yielded new insights into many previously uncharacterized microbial communities. Application of standardized practices in the study of skin microbial communities could help us understand their complex structures, functional capacities, and health associations and increase the reproducibility of the research. Here, we overview the current research in human skin microbiomes and outline challenges specific to their study. Furthermore, we provide perspectives on recent advances in methods, analytical tools and applications of skin microbiomes in medicine and forensics.

Application of Microbiome in Forensics

Recent advances in next-generation sequencing technology and improvements in bioinformatics have expanded the scope of microbiome analysis as a forensic tool. Microbiome research is concerned with the study of the compositional profile and diversity of microbial flora as well as the interactions between microbes, hosts, and the environment. It has opened up many new possibilities for forensic analysis. In this review, we discuss various applications of microbiomes in forensics, including identification of individuals, geolocation inference, post-mortem interval (PMI) estimation, and others.

Using metagenomic data to boost protein structure prediction and discovery

Over the past decade, metagenomic sequencing approaches have been providing an ever-increasing amount of protein sequence data at an astonishing rate. These constitute an invaluable source of information which has been exploited in various research fields such as the study of the role of the gut microbiota in human diseases and aging. However, only a small fraction of all metagenomic sequences collected have been functionally or structurally characterized, leaving much of them completely unexplored. Here, we review how this information has been used in protein structure prediction and protein discovery. We begin by presenting some widely used metagenomic databases and analyze in detail how metagenomic data has contributed to the impressive improvement in the accuracy of structure prediction methods in recent years. We then examine how metagenomic information can be exploited to annotate protein sequences. More specifically, we focus on the role of metagenomes in the discovery of enzymes and new CRISPR-Cas systems, and in the identification of antibiotic resistance genes. With this review, we provide an overview of how metagenomic data is currently revolutionizing our understanding of protein science.