A fast machine-learning-guided primer design pipeline for selective whole genome amplification

AI in SERS sensing moving from discriminative to generative

This perspective discusses the present and future role of artificial intelligence (AI) and machine learning (ML) in surface-enhanced Raman scattering (SERS) sensing. Our goal is to guide the reader through current applications, mainly focused on discriminative approaches aimed at developing new and improved SERS diagnostic capabilities, towards the future role of AI in SERS sensing, with the use of generative approaches to design new materials and biomaterials.

Protease and Bacillus coagulans Supplementation in a Low-Protein Diet Improves Broiler Growth, Promotes Amino Acid Transport Gene Activity, Strengthens Intestinal Barriers, and Alters the Cecal Microbial Composition

Low-protein (LPRO) diets can effectively reduce feed costs and decrease environmental pollution, making them an important pathway to enhance the sustainability of livestock production. However, they may have adverse effects on the growth performance of broiler chickens, which has limited their widespread application. This study aims to explore the impact of adding protease (PRO) to LPRO diets on the growth performance of broiler chickens, especially under conditions with or without the presence of Bacillus coagulans (BC), in order to provide theoretical support for the scientific application and promotion of LPRO feeds. We selected 432 one-day-old broiler chickens and divided them into four treatment groups, which were fed with the control (CON) diet, the LPRO diet, the PRO diet (LPRO diet with added protease), and the PAB diet (PRO diet with added BC). The LPRO group demonstrated decreased growth performance while both PRO and PAB diets resulted in a significant increase (p < 0.05). Both PRO and PAB diets significantly enhanced the expression of amino acid transport genes and tight junction genes (p < 0.05) and optimized the composition of the intestinal microbiota. Overall, LPRO diets have a detrimental effect on the growth of broiler chickens, while the PRO and PAB diets effectively counteract these negative effects by improving protein digestion, amino acid absorption, and intestinal health.

Nucleic acid detection with single-base specificity integrating isothermal amplification and light-up aptamer probes

We report a novel platform for label-free nucleic acid detection using isothermal amplification and light-up aptamer probes. This assay converts double-stranded amplicons into single-stranded targets to enable sequence-specific hybridization with split dapoxyl aptamer probes, offering attomolar sensitivity and single-base specificity.

A Novel and Rapid Selective Viral Genome Amplification and Sequencing Method for African Swine Fever Virus

African swine fever virus (ASFV) is the etiological agent of African swine fever, a highly contagious hemorrhagic disease affecting both wild boars and domestic pigs with lethality rates up to 100%. Until now, the most effective measure to prevent an outbreak of ASFV was early detection. In this situation, whole genome sequencing (WGS) allows the gathering of detailed information about the identity and epidemiology of the virus. However, due to the large genome size and complex genome ends, WGS is challenging. Current WGS workflows require either elaborate enrichment methods or are based on tiled PCR approaches, which are susceptible to genetic differences between ASFV strains. To overcome this, we developed a novel approach for WGS of ASFV, using the Phi29 DNA polymerase-based multiple displacement amplification in combination with only seven primers. Furthermore, we applied an alkaline-based DNA denaturation step to significantly increase the number of viral reads, which resolves the near-full genome of ASFV. This novel isothermal WGS approach can be used in authorized laboratories for the genomic epidemiological analysis of ASFV outbreaks caused by different genotypes.

Revealing the Genetic Diversity of Chinese Chlamydia trachomatis Strains Directly From Clinical Samples Through Selective Whole Genome Amplification

BACKGROUND

Chlamydia trachomatis is the causative agent of the most prevalent bacterial sexually transmitted infections globally. Whole genome sequencing is essential for molecular Chlamydia surveillance; however, its application is hampered by the pathogen's low abundance in clinical specimens and the expensive labor-intensive nature of existing enrichment methodologies for Chlamydia.

METHODS

We developed a targeted whole genome amplification tool termed SWITCH by integrating phi29 DNA polymerase-mediated amplification with meticulously designed primer sets to enrich the C trachomatis genome, followed by whole genome sequencing. This method underwent evaluation through testing synthetic and clinical specimens.

RESULTS

SWITCH demonstrated robust ability to achieve up to 98.3% genomic coverage of C trachomatis from as few as 26.4 genomic copies present in synthetic specimens, and it exhibited excellent performance across diverse C trachomatis serovars. Utilizing SWITCH, we directly generated 21 Chlamydia genomes from 26 clinical samples, enabling us to gain insights into the genetic relationships and phylogeny of current Chlamydia strains circulating in the country. Remarkably, this study marked the first instance of generating Chinese Chlamydia genomes directly from clinical samples.

CONCLUSIONS

SWITCH represents a practical cost-efficient approach to enrich the Chlamydia genome directly from clinical specimens, offering an efficient avenue for molecular surveillance of Chlamydia.

A novel isothermal whole genome sequencing approach for Monkeypox Virus

Monkeypox virus (MPXV) is the zoonotic agent responsible for mpox, an often-self-limiting pox-like disease. Since May 2022, an outbreak characterized by increased human-to-human transmission was detected outside the endemic regions. Whole genome sequencing (WGS) has been successfully used to keep track of viral evolution during outbreaks or for surveillance of multiple pathogens of public health significance. Current WGS protocols for MPXV are either based on metagenomic sequencing or tiled-PCR amplification. The latter allows multiplexing due to the efficient enrichment of the viral DNA, however, mutations or the presence of different clades can negatively influence genome coverage yield. Here, we present the establishment of a novel isothermal WGS method for MPXV based on Phi29 DNA polymerase-based multiple displacement amplification (MDA) properties making use of only 6 primers. This approach yielded from 88% up to 100% genome coverage using either alkaline denatured extracted DNA or clinical material as starting material, with the highest coverage generated by clinical material. We demonstrate that this novel isothermal WGS protocol is suitable for monitoring viral evolution during MPXV outbreaks and surveillance in any conventional laboratory setting.

primerForge: a Python program for identifying primer pairs capable of distinguishing groups of genomes from each other

In both molecular epidemiology and microbial ecology, it is useful to be able to categorize specific strains of microorganisms in either an ingroup or an outgroup in a given population, e.g. to distinguish a pathogenic strain of interest from its non-virulent relatives. An "ingroup" refers to a group of microbes that are the primary focus of study or interest. Conversely, an "outgroup" consists of microbes that are closely-related to, but have evolved separately from, the ingroup. While whole genome sequencing and downstream phylogenetic analyses can be employed to do this, these techniques are often slow and can be resource intensive. Additionally, the laboratory would have to sequence the whole genome to use these tools to determine whether or not a new sample is part of the ingroup or outgroup. Alternatively, polymerase chain reaction (PCR) can be used to amplify regions of genetic material that are specific to the strain(s) of interest. PCR is faster, less expensive, and more accessible than whole genome sequencing, so having a PCR-based approach can accelerate the detection of specific strain(s) of microbes and facilitate diagnoses and/or population studies.

Turning the needle into the haystack: Culture-independent amplification of complex microbial genomes directly from their native environment

High-throughput sequencing (HTS) has revolutionized microbiology, but many microbes exist at low abundance in their natural environment and/or are difficult, if not impossible, to culture in the laboratory. This makes it challenging to use HTS to study the genomes of many important microbes and pathogens. In this review, we discuss the development and application of selective whole genome amplification (SWGA) to allow whole or partial genomes to be sequenced for low abundance microbes directly from complex biological samples. We highlight ways in which genomic data generated by SWGA have been used to elucidate the population dynamics of important human pathogens and monitor development of antimicrobial resistance and the emergence of potential outbreaks. We also describe the limitations of this method and propose some potential innovations that could be used to improve the quality of SWGA and lower the barriers to using this method across a wider range of infectious pathogens.

Time series-based hybrid ensemble learning model with multivariate multidimensional feature coding for DNA methylation prediction

BACKGROUND

DNA methylation is a form of epigenetic modification that impacts gene expression without modifying the DNA sequence, thereby exerting control over gene function and cellular development. The prediction of DNA methylation is vital for understanding and exploring gene regulatory mechanisms. Currently, machine learning algorithms are primarily used for model construction. However, several challenges remain to be addressed, including limited prediction accuracy, constrained generalization capability, and insufficient learning capacity.

RESULTS

In response to the aforementioned challenges, this paper leverages the similarities between DNA sequences and time series to introduce a time series-based hybrid ensemble learning model, called Multi2-Con-CAPSO-LSTM. The model utilizes multivariate and multidimensional encoding approach, combining three types of time series encodings with three kinds of genetic feature encodings, resulting in a total of nine types of feature encoding matrices. Convolutional Neural Networks are utilized to extract features from DNA sequences, including temporal, positional, physicochemical, and genetic information, thereby creating a comprehensive feature matrix. The Long Short-Term Memory model is then optimized using the Chaotic Accelerated Particle Swarm Optimization algorithm for predicting DNA methylation.

CONCLUSIONS

Through cross-validation experiments conducted on 17 species involving three types of DNA methylation (6 mA, 5hmC, and 4mC), the results demonstrate the robust predictive capabilities of the Multi2-Con-CAPSO-LSTM model in DNA methylation prediction across various types and species. Compared with other benchmark models, the Multi2-Con-CAPSO-LSTM model demonstrates significant advantages in sensitivity, specificity, accuracy, and correlation. The model proposed in this paper provides valuable insights and inspiration across various disciplines, including sequence alignment, genetic evolution, time series analysis, and structure-activity relationships.

MultiPrime: A reliable and efficient tool for targeted next-generation sequencing

We present multiPrime, a novel tool that automatically designs minimal primer sets for targeted next-generation sequencing, tailored to specific microbiomes or genes. MultiPrime enhances primer coverage by designing primers with mismatch tolerance and ensures both high compatibility and specificity. We evaluated the performance of multiPrime using a data set of 43,016 sequences from eight viruses. Our results demonstrated that multiPrime outperformed conventional tools, and the primer set designed by multiPrime successfully amplified the target amplicons. Furthermore, we expanded the application of multiPrime to 30 types of viruses and validated the work efficacy of multiPrime-designed primers in 80 clinical specimens. The subsequent sequencing outcomes from these primers indicated a sensitivity of 94% and a specificity of 89%.