Detection of mixed-strain infections by FACS and ultra-low input genome sequencing

Dual-layered hydrogels allow complete genome recovery with nucleic acid cytometry

Targeting specific cells for sequencing is important for applications in cancer, microbiology, and infectious disease. Nucleic acid cytometry is a powerful approach for accomplishing this because it allows specific cells to be isolated based on sequence biomarkers that are otherwise impossible to detect. However, existing methods require specialized microfluidic devices, limiting adoption. Here, we describe a modified workflow that uses particle-templated emulsification and flow cytometry to conduct the essential steps of cell detection and sorting normally accomplished by microfluidics. Our microfluidic-free workflow allows facile isolation and sequencing of cells, viruses, and nucleic acids and thus provides a powerful enrichment approach for targeted sequencing applications. This article is protected by copyright. All rights reserved.

Curcumin-C3 Complexed with α-, β-cyclodextrin Exhibits Antibacterial and Antioxidant Properties Suitable for Cancer Treatments

BACKGROUND

The curcumin-C3 (cur-C3) complex obtained from Curcuma longa rhizome is a combination of three curcuminoids, namely, curcumin, dimethoxycurcumin, and bisdemethoxycurcumin. Cur and curcuminoids have been extensively researched for their wide range of therapeutic properties against inflammatory diseases, diabetes, and cancer.

OBJECTIVE

In spite of their extensive medicinal properties, cur and curcuminoids have poor solubility and bioavailability due to their hydrophobicity. This limitation can be overcome by complexing cur-C3 with natural cyclic oligosaccharides, such as Cyclodextrin (CD).

METHODS

In this study, cur-C3 and CD (α, β) inclusion complexes (ICs) were prepared with different molar ratios and characterized by nuclear magnetic resonance, Fourier transform infrared spectroscopy, X-ray diffraction, and transmission electron microscopy.

RESULTS

The cur-C3 cyclodextrin ICs showed an increased entrapment efficiency of 97.8% and improved antioxidant activity compared to cur and can be used as an antioxidant to reduce cancer-related oxidative stress. Additionally, α- CD ICs of curcumin-C3 caused an increase in growth inhibition of Staphylococcus aureus.

CONCLUSION

Our findings suggest that both α- and β-CDs are suitable carriers for cur-C3 and can be used as an effective treatment for cancer-associated oxidative stress and as a preventive treatment for nosocomial infections and pneumonia.

BacTag - a pipeline for fast and accurate gene and allele typing in bacterial sequencing data based on database preprocessing

BACKGROUND

Bacteria carry a wide array of genes, some of which have multiple alleles. These different alleles are often responsible for distinct types of virulence and can determine the classification at the subspecies levels (e.g., housekeeping genes for Multi Locus Sequence Typing, MLST). Therefore, it is important to rapidly detect not only the gene of interest, but also the relevant allele. Current sequencing-based methods are limited to mapping reads to each of the known allele reference, which is a time-consuming procedure.

RESULTS

To address this limitation, we developed BacTag - a pipeline that rapidly and accurately detects which genes are present in a sequencing dataset and reports the allele of each of the identified genes. We exploit the fact that different alleles of the same gene have a high similarity. Instead of mapping the reads to each of the allele reference sequences, we preprocess the database prior to the analysis, which makes the subsequent gene and allele identification efficient. During the preprocessing, we determine a representative reference sequence for each gene and store the differences between all alleles and this chosen reference. Throughout the analysis we estimate whether the gene is present in the sequencing data by mapping the reads to this reference sequence; if the gene is found, we compare the variants to those in the preprocessed database. This allows to detect which specific allele is present in the sequencing data. Our pipeline was successfully tested on artificial WGS E. coli, S. pseudintermedius, P. gingivalis, M. bovis, Borrelia spp. and Streptomyces spp. data and real WGS E. coli and K. pneumoniae data in order to report alleles of MLST house-keeping genes.

CONCLUSIONS

We developed a new pipeline for fast and accurate gene and allele recognition based on database preprocessing and parallel computing and performed better or comparable to the current popular tools. We believe that our approach can be useful for a wide range of projects, including bacterial subspecies classification, clinical diagnostics of bacterial infections, and epidemiological studies.