NEX-t Panel v1.0

• Support. Different library preparation approaches can be employed for RNA and DNA viruses. One approach involves the concurrent library preparation of RNA and DNA viruses, followed by subsequent hybridization capture steps. Another approach entails preparing RNA libraries and DNA libraries separately, and then mixing them for hybridization capture. Generally, for RNA libraries, there is no need to perform the step of removing of host ribosomal RNA.
• As shown in Figure, the example demonstrates the capture scenario when RNA libraries containing influenza virus (H10N3) and DNA libraries are hybridized together. A total of 15 libraries are involved, including 11 DNA libraries and 4 RNA libraries. The example library data amount was 100 Mb (totaling 9.3 Gb for all 15 libraries), with host sequences accounting for 58.3%.

• As shown in Figure 4, the detection limit for samples with varying microbial content is approximately 3 copies. In practical applications, sensitivity is mainly determined by the amount of input for library preparation. It's important to note that the library preparation process is constrained by conversion efficiency, meaning not all copies can be successfully converted.  Similarly, when the copy number is in the single digits, the success rate of multiplex amplicons'  amplification decreases.
• Furthermore, having less than 1 copy does not imply that it cannot be detected. This is due to the fact that when NEX-t Panel v1.0 features multiple probe capture regions for a single species, their copy numbers can accumulate, enhancing the detection sensitivity.

• The on-target rate of pathogens are significantly influenced by the amount of pathogens within the samples. As shown in Figure, under the same host background, as the microbial reference material is gradually diluted, the amount of data decreases proportionally, along with a decrease in on-target rate.
• Although multiple capture rounds can substantially improve on-target rate, this strategy comes with the risk of information loss (dropout). Especially when the amount of pathogen is low, the on-target rate is low and is more l sensitive to dropout. Therefore, careful consideration of the pros and cons is needed when contemplating multiple capture rounds. Additionally, from another perspective, when the pathogen genome copy numbers in the sample are in the single digits, increasing on-target rate merely involves repetitive sequencing of these few copies, yielding limited additional useful information.

• In general, achieving complete probe coverage of pathogen microbiome genomes is impractical. On one hand, designing probes for a single bacterial species can result in hundreds of thousands of probes when considering sequence polymorphism beyond reference genomes.  On the other hand, to prevent off-target effects when there is similarity between pathogenic and host sequences, certain regions must be excluded. Therefore, NEX-t Panel v1.0 emphasizes designing the fewest probes to enable the broadest range of pathogen analysis, resulting in a significantly streamlined panel size compared to tNGS schemes with millions of probes in hybrid capture.
• The number of probes can be roughly equivalent to the number of amplicons in multiplex PCR. However, due to the higher tolerance of probes and the ability to capture sequences flanking the probe, a certain number of probes can provide more diverse information compared to a similar number of multiplex amplicons.
• Compared to multiplex PCR, expanding a hybrid capture panel is simpler as it only requires adding probes. Therefore, NEX-t Panel v1.0 can be conveniently customized and upgraded through combination.

In pathogen detection, SE sequencing mode is more time-efficient and is therefore more commonly used than PE mode. Regardless of the sequencing mode chosen, as long as a sufficient number of reads is detected, it can be used for pathogen analysis and will not affect the final result interpretation. When using SE50/75 sequencing mode, there is no need to increase the sequencing data volume. The current demo data, actually in PE150 mode, can be effectively analyzed as if it were SE50 or SE100 data, ensuring reliable pathogen detection.

The actual amount of data obtained from sequencing depends on the content of pathogenic microorganisms in clinical specimens. Whether a report is generated is based on the number of supporting reads detected for the pathogen, and is not related to the total amount of data obtained from sequencing. If a predicted credible pathogenic microorganism is shown as undetected in the report, even with sufficient data, it may be advisable to increase the data volume for further bioinformatics analysis or perform verification using PCR. Conversely, if the sequencing data volume is very low but enough supporting data is detected for a pathogen microorganism, a report may still be generated.

To obtain rapid identification results of pathogenic microorganisms in clinical specimens, it is recommended to use BGI's DNBSEQ-G99 (SE100) / DNBSEQ-E25 (SE100), which allows for a minimum run time of 5 hours, or Illumina MiniSeq/MiSeq (SE100), also with a minimum run time of 5 hours.

The complete tNGS pathogen microorganism detection process includes nucleic acid extraction (1.5 hr), RNA/DNA library preparation(~5.5/2.5 hr), hybrid capture (~4 hr), NGS sequencing (~5 hr), bioinformatics analysis, and automated report interpretation (~0.5 hr), with a total estimated time of approximately 13.5 to 16.5 hours.

NEX-t Panel v1.0 targets a series of characteristic sequences selected from the genomes of hundreds of pathogens including viruses, bacteria, fungi and parasites. It covers a rich range of content including 16S/ITS, housekeeping genes, drug-resistant related genes, and more. A single test encompasses over 450 genera and comprehensively covers 7000+ species of pathogenic microorganisms, meeting more than 99% of clinical pathogen detection needs (see attached species list for details).

The quality of nucleic acid extraction is crucial in determining the success of high-throughput sequencing tests. Different laboratories should establish comprehensive nucleic acid extraction procedures. Firstly, the selected nucleic acid extraction reagents should be validated to ensure the efficiency and integrity of nucleic acid extraction. Quantitative measurements should be performed on each extracted nucleic acid sample to ensure that they meet the requirements for subsequent experiments. Simultaneously, standards for qualified nucleic acid samples should be established.

Nucleic Acid Quality Verification:

(1) High-quality DNA should have an A260/A280 ratio between 1.7 ~1.9, and A260/A230 > 2. DNA quality can be verified by 1% agarose gel electrophoresis (no impurities, no smearing, and no protein contamination in the background).

(2) DNA integrity should be assessed using techniques such as Agilent 2100 Bioanalyzer. If the majority of fragments are below 200 nt (except for plasma cell-free DNA, which may be 140 nt), it indicates severe DNA degradation and requires re-extraction.

(3) High-quality RNA should have an A260/A280 ratio between 1.8 ~ 2.0, with an A260/A230 ratio greater than 2.

(4) Small amounts of nucleic acid should be quantified using the Qubit fluorescence dye method.

In summary, during clinical sample collection, it is essential to ensure an adequate amount of the sample for nucleic acid extraction to obtain higher abundance nucleic acid samples. The higher the abundance of pathogenic microorganisms in the libraries prepared for tNGS, the lower the limit of detection (LOD) in tNGS detecting. This allows for efficient detection of low-load pathogenic microorganisms.

This information is primarily sourced from "Expert Consensus on the Application of High-Throughput Sequencing Technology in the Diagnosis of Mycobacterial Diseases" and "Expert Consensus on Standardizing Clinical Applications of High-Throughput Metagenomic Sequencing for Pathogen Detection."

The quality of clinical specimens directly affects the detection results. The extent to which different specimen types are influenced by colonizing microorganisms varies, leading to differences in the reliability of tNGS detection results.

The collection requirements for different types of clinical specimens

The primary information is sourced from the Expert Consensus on the Application of High-Throughput Sequencing Technology in the Diagnosis of Mycobacterial Diseases.