Mining Public Metagenomes for Environmental Surveillance of Parasites: A Proof of Principle

A Large-Scale Study into Protist-Animal Interactions Based on Public Genomic Data Using DNA Barcodes

With the birth of next-generation sequencing (NGS) technology, genomic data in public databases have increased exponentially. Unfortunately, exogenous contamination or intracellular parasite sequences in assemblies could confuse genomic analysis. Meanwhile, they can provide a valuable resource for studies of host-microbe interactions. Here, we used a strategy based on DNA barcodes to scan protistan contamination in the GenBank WGS/TSA database. The results showed a total of 13,952 metazoan/animal assemblies in GenBank, where 17,036 contigs were found to be protistan contaminants in 1507 assemblies (10.8%), with even higher contamination rates in taxa of Cnidaria (150/281), Crustacea (237/480), and Mollusca (107/410). Taxonomic analysis of the protists derived from these contigs showed variations in abundance and evenness of protistan contamination across different metazoan taxa, reflecting host preferences of Apicomplexa, Ciliophora, Oomycota and Symbiodiniaceae for mammals and birds, Crustacea, insects, and Cnidaria, respectively. Finally, mitochondrial proteins COX1 and CYTB were predicted from these contigs, and the phylogenetic analysis corroborated the protistan origination and heterogeneous distribution of the contaminated contigs. Overall, in this study, we conducted a large-scale scan of protistan contaminant in genomic resources, and the protistan sequences detected will help uncover the protist diversity and relationships of these picoeukaryotes with Metazoa.

Point of care diagnostics for Cryptosporidium: new and emerging technologies

PURPOSE OF REVIEW

Although Cryptosporidium detection and typing techniques have improved dramatically in recent years, relatively little research has been conducted on point of care (POC) detection and typing tools. Therefore, the main purpose of the present review is to summarize and evaluate recent and emerging POC diagnostic methods for Cryptosporidium spp.

RECENT FINDINGS

Microscopy techniques such as light-emitting diode fluorescence microscopy with auramine-phenol staining (LED-AP), still have utility for (POC) diagnostics but require fluorescent microscopes and along with immunological-based techniques, suffer from lack of specificity and sensitivity. Molecular detection and typing tools offer higher sensitivity, specificity and speciation, but are currently too expensive for routine POC diagnostics. Isothermal amplification methods such as loop-mediated isothermal amplification (LAMP) or recombinase polymerase amplification (RPA) including a commercially available LAMP kit have been developed for Cryptosporidium but are prone to false positives. Clustered regularly interspaced short palindromic repeats (CRISPR)-Cas diagnostic technologies (CRISPRDx) have recently been combined with isothermal amplification to increase its specificity and sensitivity for detection and typing. Other emerging technologies including amplification-free CRISPR detection methods are currently being developed for Cryptosporidium using a smartphone to read the results.

SUMMARY

Many challenges are still exist in the development of POC diagnostics for Cryptosporidium. The ideal POC tool would be able to concentrate the pathogen prior to detection and typing, which is complicated and research in this area is still very limited. In the short-term, CRISPR-powered isothermal amplification lateral flow tools offer the best opportunity for POC Cryptosporidium species and subtype detection, with a fully integrated autonomous biosensor for the long-term goal.

Valorization as a biofertilizer of an agricultural residue leachate: Metagenomic characterization and growth promotion test by PGPB in the forage plant Medicago sativa (alfalfa)

The abuse of chemical fertilizers in intensive agriculture has turned out in the contamination of ground and the soil on which they are applied. Likewise, the generation, storage, and destruction of plant residues from the agri-food industry poses a threat to the environment and human health. The current situation of growing demand for food implies the urgent need to find sustainable alternatives to chemical fertilizers and the management of agricultural waste. Valorization of this plant residue to produce natural biofertilizers using microbiological treatments is presented as a sustainable alternative. The microbial activity allows the transformation into simple molecules that are easily absorbed by plants, as well as the stimulation of plant growth. This double direct and indirect action induced significant increases against the variables of germination, viability, and biomass (dry weight). To guarantee biosafety, it is necessary to use new bio-technological tools, such as metagenomics, which allow the taxonomic analysis of microbial communities, detecting the absence of pathogens. In the present paper, a physicochemical and metagenomic characterization of a fertilizer obtained from agricultural plant waste valorization is carried out. Likewise, fertigation treatments were tested to which the Plant Growth Promoting Bacteria (PGPB) Pseudomonas agronomica and Bacillus pretiosus were added, both independently and in consortium. Metagenomic analysis has identified taxa belonging to the kingdoms Bacteria and Archaea; 10 phyla, 25 families, 32 genera and 34 species, none of them previously described as pathogenic. A 1/512 dilution of the fertilizer increased the germination rate of Medicago sativa (alfalfa) by 16% at 144 h, compared to the treatment without fertilizer. Both the fertilizer and the addition of PGPB in a double direct and indirect action induced significant increases against the variables of germination, viability, and biomass (dry weight). Therefore, the use of an agricultural residue is proposed, which after the addition of two new species is transformed into a biofertilizer that significantly induces plant growth in Mendicago sativa plants.

An Update on Zoonotic Cryptosporidium Species and Genotypes in Humans

The enteric parasite, Cryptosporidium is a major cause of diarrhoeal illness in humans and animals worldwide. No effective therapeutics or vaccines are available and therefore control is dependent on understanding transmission dynamics. The development of molecular detection and typing tools has resulted in the identification of a large number of cryptic species and genotypes and facilitated our understanding of their potential for zoonotic transmission. Of the 44 recognised Cryptosporidium species and >120 genotypes, 19 species, and four genotypes have been reported in humans with C. hominis, C. parvum, C. meleagridis, C. canis and C. felis being the most prevalent. The development of typing tools that are still lacking some zoonotic species and genotypes and more extensive molecular epidemiological studies in countries where the potential for transmission is highest are required to further our understanding of this important zoonotic pathogen. Similarly, whole-genome sequencing (WGS) and amplicon next-generation sequencing (NGS) are important for more accurately tracking transmission and understanding the mechanisms behind host specificity.

State-of-the-Art Techniques for Diagnosis of Medical Parasites and Arthropods

Conventional methods such as microscopy have been used to diagnose parasitic diseases and medical conditions related to arthropods for many years. Some techniques are considered gold standard methods. However, their limited sensitivity, specificity, and accuracy, and the need for costly reagents and high-skilled technicians are critical problems. New tools are therefore continually being developed to reduce pitfalls. Recently, three state-of-the-art techniques have emerged: DNA barcoding, geometric morphometrics, and artificial intelligence. Here, data related to the three approaches are reviewed. DNA barcoding involves an analysis of a barcode sequence. It was used to diagnose medical parasites and arthropods with 95.0% accuracy. However, this technique still requires costly reagents and equipment. Geometric morphometric analysis is the statistical analysis of the patterns of shape change of an anatomical structure. Its accuracy is approximately 94.0-100.0%, and unlike DNA barcoding, costly reagents and equipment are not required. Artificial intelligence technology involves the analysis of pictures using well-trained algorithms. It showed 98.8-99.0% precision. All three approaches use computer programs instead of human interpretation. They also have the potential to be high-throughput technologies since many samples can be analyzed at once. However, the limitation of using these techniques in real settings is species coverage.