Development and evaluation of a meat mitochondrial metagenomic (3MG) method for composition determination of meat from fifteen mammalian and avian species

Background Bioassessment and biomonitoring of meat products are aimed at identifying and quantifying adulterants and contaminants, such as meat from unexpected sources and microbes. Several methods for determining the biological composition of mixed samples have been used, including metabarcoding, metagenomics and mitochondrial metagenomics. In this study, we aimed to develop a method based on next-generation DNA sequencing to estimate samples that might contain meat from 15 mammalian and avian species that are commonly related to meat bioassessment and biomonitoring. Results In this project, we found the meat composition from 15 species could not be identified with the metabarcoding approach because of the lack of universal primers or insufficient discrimination power. Consequently, we developed and evaluated a meat mitochondrial metagenomics (3MG) method. The 3MG method has four steps: (1) extraction of sequencing reads from mitochondrial genomes (mitogenomes); (2) assembly of mitogenomes; (3) mapping of mitochondrial reads to the assembled mitogenomes; and (4) biomass estimation based on the number of uniquely mapped reads. The method was implemented in a python script called 3MG. The analysis of simulated datasets showed that the method can determine contaminant composition at a proportion of 2% and the relative error was < 5%. To evaluate the performance of 3MG, we constructed and analysed mixed samples derived from 15 animal species in equal mass. Then, we constructed and analysed mixed samples derived from two animal species (pork and chicken) in different ratios. DNAs were extracted and used in constructing 21 libraries for next-generation sequencing. The analysis of the 15 species mix with the method showed the successful identification of 12 of the 15 (80%) animal species tested. The analysis of the mixed samples of the two species revealed correlation coefficients of 0.98 for pork and 0.98 for chicken between the number of uniquely mapped reads and the mass proportion. Conclusion To the best of our knowledge, this study is the first to demonstrate the potential of the non-targeted 3MG method as a tool for accurately estimating biomass in meat mix samples. The method has potential broad applications in meat product safety.

Bacterial genomic epidemiology with mixed samples

Genomic epidemiology is a tool for tracing transmission of pathogens based on whole-genome sequencing. We introduce the mGEMS pipeline for genomic epidemiology with plate sweeps representing mixed samples of a target pathogen, opening the possibility to sequence all colonies on selective plates with a single DNA extraction and sequencing step. The pipeline includes the novel mGEMS read binner for probabilistic assignments of sequencing reads, and the scalable pseudoaligner Themisto. We demonstrate the effectiveness of our approach using closely related samples in a nosocomial setting, obtaining results that are comparable to those based on single-colony picks. Our results lend firm support to more widespread consideration of genomic epidemiology with mixed infection samples.

Analysis on Spectral Matching of Biochemical Component for Rice

The protein, starch and amylose are three important indexes to characterize rice quality. The starch, crude protein and amylose of rice were extracted by experiments. The hyperspectral reflectance of starch, crude protein and amylose, their mixed samples and rice samples were determined by a ASD FieldSpec Pro FR™ The spectral characteristics of starch, crude protein, amylose and their correlation with component content were analyzed by using spectral matching technique and multivariate statistical method. The results showed that the spectra of three biochemical components were significantly different, and the spectral peaks and valleys of the mixed samples showed “red shift” or “blue shift”. The contents (%) of crude protein, starch and amylose in rice flour were significantly related to the absorption area S between 2020nm and 2235nm on their spectral curve. The results showed that the hyperspectral method could be used to estimate the contents of crude protein, starch and amylose content in rice, and then to detect rice quality.

Determination of composition of mixed biological samples using laser-induced fluorescence and combined classification/regression models

Laser-induced fluorescence (LIF) provides the ability to distinguish organic materials by a fast and distant in situ analysis. When detecting the substances directly in the environment, e.g., in an aerosol cloud or on surfaces, additional fluorescence signals of other fluorophores occurring in the surrounding are expected to mix with the desired signal. We approached this problem with a simplified experimental design for an evaluation of classification algorithms. An upcoming question for enhanced identification capabilities is the case of mixed samples providing different signals from different fluorophores. For this work, mixtures of up to four common fluorophores (NADH, FAD, tryptophan and tyrosine) were measured by a dual-wavelength setup and spectrally analyzed. Classification and regression are conducted with neural networks and show an excellent performance in predicting the ratios of the selected ingredients.

Mycobacterium intracellulare subsp. chimaera from Cardio Surgery Heating-Cooling Units and from Clinical Samples in Israel Are Genetically Unrelated

Non-tuberculous mycobacteria (NTM) are opportunistic pathogens that cause illness primarily in the elderly, in the immunocompromised or in patients with underlying lung disease. Since 2013, a global outbreak of NTM infection related to heater-cooler units (HCU) used in cardio-thoracic surgery has been identified. This outbreak was caused by a single strain of Mycobacterium intracellulare subsp. chimaera. In order to estimate the prevalence of this outbreak strain in Israel, we sampled Mycobacterium intracellulare subsp. chimaera from several HCU machines in Israel, as well as from patients, sequenced their genomes and compared them to the outbreak strain. The presence of mixed mycobacteria species in the samples complicated the analysis of obtained sequences. By applying a metagenomic binning strategy, we were able to obtain, and characterize, genomes of single strains from the mixed samples. Mycobacterium intracellulare subsp. chimaera strains were compared to each other and to previously reported genomes from other countries. The strain causing the outbreak related to the HCU machines was identified in several such machines in Israel but not in any clinical sample.

Licorice Germplasm Resources Identification Using DNA Barcodes Inner-Variants

Based on the gradual transformation from wild growth to artificial cultivation, the accurate authentication of licorice seeds contributes to the first committed step of its quality control and is pivotal to ensure the clinical efficacy of licorice. However, it is still challenging to obtain genetically stable licorice germplasm resources due to the multi-source, multi-heterozygous, polyploid, and hybrid characteristics of licorice seeds. Here, a new method for determining the heterozygosity of licorice seed mixture, based on the various sites, and finding the composition characteristics of licorice seed is preliminarily designed and proposed. Namely, high-throughput full-length multiple DNA barcodes(HFMD), based on ITS multi-copy variation exist, the full-length amplicons of ITS2, psbA-trnH and ITS are directly sequenced by rDNA through the next-generation sequence(NGS) and single-molecule real-time (SMRT) technologies. By comparing the three sequencing methods, our results proved that SMRT sequencing successfully identified the complete gradients of complex mixed samples with the best performance. Meanwhile, HFMD is a brilliant and feasible method for evaluating the heterozygosity of licorice seeds. It shows a perfect interpretation of DNA barcoding and can be applied in multi-base multi-heterozygous and polyploid species.

Arrowroot and Cassava Mixed Starch Products Identification by Raman Analysis with Chemometrics

Food frauds present a major problem in the foodstuff industry. Arrowroot and cassava may be targeted in adulteration and falsification processes. Raman analysis combined with chemometric techniques was proposed to identify the mixing and adulteration of these foodstuffs in commercial products. 67 cassava and 5 arrowroot samples were prepared in laboratory. 21 cassava and 5 arrowroot commercial samples were purchased in local stores. Raman assays were performed in the range of 400 to 2300 cm−1. Principal component analysis with K-means clustering was used to identify the adulteration of these products. It was possible to observe the separation of three different groups in the data, these groups labelled group 1, 2 and 3 were correspondent to cassava-like samples, mixed samples, and arrowroot-like samples, respectively. Despite the visual analysis related to sensory characteristics and the visual analysis of each Raman spectrum of cassava and arrowroot not being able to differentiate these foodstuffs, the chemometric approaches with the Raman specters data were able to identify which samples were pure arrowroot, pure cassava and which were mixed products. The proposed approach showed to be an effective tool in the investigation of fraud for arrowroot and cassava.

Enhancement of Bentonite Materials with Cement for Gamma-Ray Shielding Capability

The gamma-ray shielding ability of various Bentonite–Cement mixed materials from northeast Egypt have been examined by determining their theoretical and experimental mass attenuation coefficients, μm (cm2g−1), at photon energies of 59.6, 121.78, 344.28, 661.66, 964.13, 1173.23, 1332.5 and 1408.01 keV emitted from 241Am, 137Cs, 152Eu and 60Co point sources. The μm was theoretically calculated using the chemical compositions obtained by Energy Dispersive X-ray Analysis (EDX), while a NaI (Tl) scintillation detector was used to experimentally determine the μm (cm2g−1) of the mixed samples. The theoretical values are in acceptable agreement with the experimental calculations of the XCom software. The linear attenuation coefficient (μ), mean free path (MFP), half-value layer (HVL) and the exposure buildup factor (EBF) were also calculated by knowing the μm values of the examined samples. The gamma-radiation shielding ability of the selected Bentonite–Cement mixed samples have been studied against other puplished shielding materials. Knowledge of various factors such as thermo-chemical stability, availability and water holding capacity of the bentonite–cement mixed samples can be analyzed to determine the effectiveness of the materials to shield gamma rays.

Screening High-Risk Groups and the General Population for SARS-CoV-2 Nucleic Acids in a Mobile Biosafety Laboratory

The Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2) pandemic has challenged public health systems worldwide. Therefore, large-scale testing capacity is extremely important diagnosis and exclusion diagnosis. However, fixed laboratories are limited or far away from remote areas. Fortunately, MBS-Lab is characterized by high mobility and rapid on-site detection of SARS-CoV-2 nucleic acid. MBS-Lab was first used in northern Australia during a melioidosis outbreak in 1997. The MBS-Lab and a well-trained diagnostic team were dispatched to Dongchang District, Tonghua City, Jilin Province, China to assist the SARS-CoV-2 virus screening and diagnosis on January 17, 2021. Altogether, 93,952 oropharyngeal swabs samples were collected and tested among the high-risk groups and the general population in Dongchang District. Two single samples were identified as positive in the second turn screening. In the second turn screening, 3 mixed samples (10 in 1) were identified as positive; 10 mixed samples were identified as positive in the third turn screening. By resampling again, one and four cases were identified as positive, respectively. The positive cases were properly isolated and treated in hospital and avoided to visit family members, friends, colleagues and any other persons. Through this way of large-scale screening, human-human spread of SARS-CoV-2 can be effectively avoided. In addition, all staff members strictly executed multiple safety precautions and reduce exposure risks. In the end, none of the staffs was infected with SARS-CoV-2 virus or other pathogens. As an emergency facility for infectious disease control, the MBS-Lab satisfies the requirements of ports and other remote areas far from fixed laboratories and supplements the capabilities of fixed laboratories.

Mycobacterium chimaera from Cardio Surgery Heating-Cooling Units and from Clinical Samples in Israel are Genetically Unrelated

Non-tuberculous mycobacteria (NTM) are opportunistic pathogens that cause illness primarily in the elderly, in the immunocompromised or in patients with underlying lung disease. Mycobacterium chimaera is a NTM species belonging to the M. avium Complex (MAC) group of species. Since 2013, a global outbreak of M. chimaera infection related to heater-cooler units (HCU) used in cardio-thoracic surgery has been identified. This outbreak was caused by a single strain of M. chimaera. In order to estimate the prevalence of this outbreak strain in Israel, we sampled M. chimaera from several HCU machines in Israel, as well as from patients, sequenced their genomes and compared them to the outbreak strain. The presence of mixed mycobacteria species in the samples complicated the analysis of obtained sequences. By applying a metagenomic binning strategy, we were able to obtain genomes of single strains from the mixed samples, and characterized them. M. chimaera strains were compared to each other and to previously reported genomes from other countries. The strain causing the outbreak related to the HCU machines was identified in several such machines in Israel but not in any of the clinical samples.