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Mousavi-Sagharchi SMA, Afrazeh E, Seyyedian-Nikjeh SF, Meskini M, Doroud D, Siadat SD. New insight in molecular detection of Mycobacterium tuberculosis. AMB Express 2024; 14:74. [PMID: 38907086 PMCID: PMC11192714 DOI: 10.1186/s13568-024-01730-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2023] [Accepted: 06/06/2024] [Indexed: 06/23/2024] Open
Abstract
Mycobacterium tuberculosis, the causative agent of tuberculosis, is a pathogenic bacterium that has claimed millions of lives since the Middle Ages. According to the World Health Organization's report, tuberculosis ranks among the ten deadliest diseases worldwide. The presence of an extensive array of genes and diverse proteins within the cellular structure of this bacterium has provided us with a potent tool for diagnosis. While the culture method remains the gold standard for tuberculosis diagnosis, it is possible that molecular diagnostic methods, emphasis on the identification of mutation genes (e.g., rpoB and gyrA) and single nucleotide polymorphisms, could offer a safe and reliable alternative. Over the past few decades, as our understanding of molecular genetics has expanded, methods have been developed based on gene expansion and detection. These methods typically commence with DNA amplification through nucleic acid targeted techniques such as polymerase chain reaction. Various molecular compounds and diverse approaches have been employed in molecular assays. In this review, we endeavor to provide an overview of molecular assays for the diagnosis of tuberculosis with their properties (utilization, challenges, and functions). The ultimate goal is to explore the potential of replacing traditional bacterial methods with these advanced molecular diagnostic techniques.
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Affiliation(s)
| | - Elina Afrazeh
- Department of Marine Biology, Faculty of Marine Science, Khorramshahr University of Marine Science and Technology, Khorramshahr, Iran
| | | | - Maryam Meskini
- Department of Mycobacteriology and Pulmonary Research, Pasteur Institute of Iran, Tehran, Iran.
- Microbiology Research Center (MRC), Pasteur Institute of Iran, Tehran, Iran.
- Department of Genetics, Faculty of Natural and Agricultural Sciences, University of the Free State, Bloemfontein, 9301, South Africa.
- Student Research Committee, Pasteur Institute of Iran, Tehran, Iran.
| | - Delaram Doroud
- Department of Immunotherapy and Leishmania Vaccine Research, Pasteur Institute of Iran, Tehran, Iran
| | - Seyed Davar Siadat
- Department of Mycobacteriology and Pulmonary Research, Pasteur Institute of Iran, Tehran, Iran.
- Microbiology Research Center (MRC), Pasteur Institute of Iran, Tehran, Iran.
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Aneli S, Fariselli P, Chierto E, Bini C, Robino C, Birolo G. Recombulator-X: A fast and user-friendly tool for estimating X chromosome recombination rates in forensic genetics. PLoS Comput Biol 2023; 19:e1011474. [PMID: 37721960 PMCID: PMC10538763 DOI: 10.1371/journal.pcbi.1011474] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2023] [Revised: 09/28/2023] [Accepted: 08/28/2023] [Indexed: 09/20/2023] Open
Abstract
Genetic markers (especially short tandem repeats or STRs) located on the X chromosome are a valuable resource to solve complex kinship cases in forensic genetics in addition or alternatively to autosomal STRs. Groups of tightly linked markers are combined into haplotypes, thus increasing the discriminating power of tests. However, this approach requires precise knowledge of the recombination rates between adjacent markers. The International Society of Forensic Genetics recommends that recombination rate estimation on the X chromosome is performed from pedigree genetic data while taking into account the confounding effect of mutations. However, implementations that satisfy these requirements have several drawbacks: they were never publicly released, they are very slow and/or need cluster-level hardware and strong computational expertise to use. In order to address these key concerns we developed Recombulator-X, a new open-source Python tool. The most challenging issue, namely the running time, was addressed with dynamic programming techniques to greatly reduce the computational complexity of the algorithm. Compared to the previous methods, Recombulator-X reduces the estimation times from weeks or months to less than one hour for typical datasets. Moreover, the estimation process, including preprocessing, has been streamlined and packaged into a simple command-line tool that can be run on a normal PC. Where previous approaches were limited to small panels of STR markers (up to 15), our tool can handle greater numbers (up to 100) of mixed STR and non-STR markers. In conclusion, Recombulator-X makes the estimation process much simpler, faster and accessible to researchers without a computational background, hopefully spurring increased adoption of best practices.
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Affiliation(s)
- Serena Aneli
- Department of Public Health Sciences and Pediatrics, University of Turin, Turin, Italy
| | - Piero Fariselli
- Department of Medical Sciences, University of Turin, Turin, Italy
| | - Elena Chierto
- Department of Public Health Sciences and Pediatrics, University of Turin, Turin, Italy
| | - Carla Bini
- Department of Medical and Surgical Sciences, Section of Legal Medicine, University of Bologna, Bologna, Italy
| | - Carlo Robino
- Department of Public Health Sciences and Pediatrics, University of Turin, Turin, Italy
- S.C. Medicina Legale, AOU Città della Salute e della Scienza, Turin, Italy
| | - Giovanni Birolo
- Department of Medical Sciences, University of Turin, Turin, Italy
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Cui W, Chen M, Yang Y, Cai M, Lan Q, Xie T, Zhu B. Applications of 1993 single nucleotide polymorphism loci in forensic pairwise kinship identifications and inferences. Forensic Sci Int Genet 2023; 65:102889. [PMID: 37247510 DOI: 10.1016/j.fsigen.2023.102889] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Revised: 04/19/2023] [Accepted: 05/11/2023] [Indexed: 05/31/2023]
Abstract
Kinship testing plays critical roles in criminal investigations, missing person searches, civil disputes, as well as identifying disaster victims. The existing commonly used short tandem repeat (STR) loci have limited effectiveness in the identification of second-degree and more distant kinships. In this study, a total of 1993 SNP loci of 119 Chinese Han individuals from eight families were sequenced on the MGISEQ-2000RS platform. The system powers of this panel for kinship identifications were evaluated based on both the likelihood ratio (LR) and identical by state (IBS) methods. The results indicated that this panel could be used as an effective tool to kinship analyses including paternity testing, full sibling testing, second-degree kinships, and first cousin kinship analyses. Both the LR and IBS methods could be applied in distinguishing first-degree and second-degree pairs from unrelated individuals. Based on the 1993 SNP loci, LR>1000 and LR<0.001 are recommended as the thresholds of identifying first-cousin kinships from unrelated individuals, and the system power of such thresholds was 0.9470. Besides, kinship coefficients for different kinship pairs were estimated and then were used to predict the kinships for pairwise individuals. This panel performs an effective kinship inference power for the predictions of first-degree, second-degree kinships and unrelated individual pairs, while presenting low sensitivity in the prediction of first-cousin kinships.
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Affiliation(s)
- Wei Cui
- Guangzhou Key Laboratory of Forensic Multi-Omics for Precision Identification, School of Forensic Medicine, Southern Medical University, Guangzhou, China
| | - Man Chen
- Guangzhou Key Laboratory of Forensic Multi-Omics for Precision Identification, School of Forensic Medicine, Southern Medical University, Guangzhou, China
| | - Yan Yang
- Golden Bridge Big Data Technology Co., LTD, Beijing, China
| | - Meiming Cai
- Guangzhou Key Laboratory of Forensic Multi-Omics for Precision Identification, School of Forensic Medicine, Southern Medical University, Guangzhou, China
| | - Qiong Lan
- Guangzhou Key Laboratory of Forensic Multi-Omics for Precision Identification, School of Forensic Medicine, Southern Medical University, Guangzhou, China; Microbiome Medicine Center, Department of Laboratory Medicine, Zhujiang Hospital, Southern Medical University, Guangzhou, Guangdong, China
| | - Tong Xie
- Guangzhou Key Laboratory of Forensic Multi-Omics for Precision Identification, School of Forensic Medicine, Southern Medical University, Guangzhou, China.
| | - Bofeng Zhu
- Guangzhou Key Laboratory of Forensic Multi-Omics for Precision Identification, School of Forensic Medicine, Southern Medical University, Guangzhou, China; Microbiome Medicine Center, Department of Laboratory Medicine, Zhujiang Hospital, Southern Medical University, Guangzhou, Guangdong, China.
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Yagasaki K, Nishida N, Mabuchi A, Tokunaga K, Fujimoto A. Development of a novel microarray data analysis tool without normalization for genotyping degraded forensic DNA. Forensic Sci Int Genet 2023; 65:102885. [PMID: 37137205 DOI: 10.1016/j.fsigen.2023.102885] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2022] [Revised: 04/13/2023] [Accepted: 04/27/2023] [Indexed: 05/05/2023]
Abstract
Since the arrest of the Golden State Killer in the US in April 2018, forensic geneticists have been increasingly interested in the investigative genetic genealogy (IGG) method. While this method has already been in practical use as a powerful tool for criminal investigation, we have yet to know well the limitations and potential risks. In this current study, we performed an evaluation study focusing on degraded DNA using the Affymetrix Genome-Wide Human SNP Array 6.0 platform (Thermo Fisher Scientific). We revealed one of the potential problems that occur during SNP genotype determination using a microarray-based platform. Our analysis results indicated that the SNP profiles derived from degraded DNA contained many false heterozygous SNPs. In addition, it was confirmed that the total amount of probe signal intensity on microarray chips derived from degraded DNA decreased significantly. Because the conventional analysis algorithm performs normalization during genotype determination, we concluded that noise signals could be genotype-called. To address this issue, we proposed a novel microarray data analysis method without normalization (nMAP). Although the nMAP algorithm resulted in a low call rate, it substantially improved genotyping accuracy. Finally, we confirmed the usefulness of the nMAP algorithm for kinship inferences. These findings and the nMAP algorithm will make a contribution to the advance of the IGG method.
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Affiliation(s)
- Kayoko Yagasaki
- Department of Human Genetics, Graduate School of Medicine, The University of Tokyo, 7-3-1, Hongo, Bunkyo Ward, Tokyo 113-0033, Japan; Forensic Science Laboratory, Tokyo Metropolitan Police Department, 3-35-21, Shakujiidai, Nerima Ward, Tokyo 177-0045, Japan.
| | - Nao Nishida
- Department of Human Genetics, Graduate School of Medicine, The University of Tokyo, 7-3-1, Hongo, Bunkyo Ward, Tokyo 113-0033, Japan; Genome Medical Science Project, National Center for Global Health and Medicine, 1-7-1, Kohnodai, Ichikawa, Chiba, 272-8516, Japan
| | - Akihiko Mabuchi
- Department of Human Genetics, Graduate School of Medicine, The University of Tokyo, 7-3-1, Hongo, Bunkyo Ward, Tokyo 113-0033, Japan
| | - Katsushi Tokunaga
- Department of Human Genetics, Graduate School of Medicine, The University of Tokyo, 7-3-1, Hongo, Bunkyo Ward, Tokyo 113-0033, Japan; Genome Medical Science Project, National Center for Global Health and Medicine, 1-21-1, Toyama, Shinjuku word, Tokyo 162-8655, Japan
| | - Akihiro Fujimoto
- Department of Human Genetics, Graduate School of Medicine, The University of Tokyo, 7-3-1, Hongo, Bunkyo Ward, Tokyo 113-0033, Japan
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Application of Forensic DNA Phenotyping for Prediction of Eye, Hair and Skin Colour in Highly Decomposed Bodies. Healthcare (Basel) 2023; 11:healthcare11050647. [PMID: 36900653 PMCID: PMC10000573 DOI: 10.3390/healthcare11050647] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Revised: 02/18/2023] [Accepted: 02/21/2023] [Indexed: 02/25/2023] Open
Abstract
In the last few years, predicting externally visible characteristics (EVCs) by adopting informative DNA molecular markers has become a method in forensic genetics that has increased its value, giving rise to an interesting field called "Forensic DNA Phenotyping" (FDP). The most meaningful forensic applications of EVCs prediction are those in which, having only a DNA sample isolated from highly decomposed remains, it is essential to reconstruct the physical appearance of a person. Through this approach, we set out to evaluate 20 skeletal remains of Italian provenance in order to associate them with as many cases of missing persons as possible. To achieve the intended goal, in this work we applied the HIrisPlex-S multiplex system through the conventional short tandem repeats (STR) method to confirm the expected identity of subjects by evaluating phenotypic features. To investigate the reliability and accuracy of the DNA-based EVCs prediction, pictures of the cases were compared as they were available to researchers. Results showed an overall prediction accuracy greater than 90% for all three phenotypic features-iris, hair, and skin colour-at a probability threshold of 0.7. The experimental analysis showed inconclusive results in only two cases; this is probably due to the characteristics of subjects who had an intermediate eye and hair colour, for which the DNA-based system needs to improve the prediction accuracy.
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Feng Y, Wang T, Yang Y, You J, He K, Zhang H, Wang Q, Yang M, Huang J, Ren Z, Jin X. Genetic features and phylogenetic relationship analyses of Guizhou Han population residing in Southwest China via 38 X-InDels. PeerJ 2023; 11:e14964. [PMID: 36915656 PMCID: PMC10007965 DOI: 10.7717/peerj.14964] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2022] [Accepted: 02/06/2023] [Indexed: 03/11/2023] Open
Abstract
Background The insertion/deletion polymorphism (InDel), an ideal forensic genetic marker with a low spontaneous mutation rate and small amplification product fragments, is widely distributed in the genome, combining the advantages of STR and SNP genetic markers. The X-chromosome has high application value in complex paternity testing, and it is an excellent system for evaluating population admixture and studying evolutionary anthropology. However, further research is needed on the population genetics of X-chromosome InDels (X-InDels). Methods In this article, a system composed of 38 X-InDel loci was utilized to analyse and evaluate the forensic parameters of the Guizhou Han population in order to explore its forensic application efficiency. Results The results showed that expected heterozygosities spanned from 0.0189 to 0.5715, and the cumulative power of discrimination of the 32 X-InDels and three linkage blocks was 0.9999999954 and 0.999999999999741 for males and females, respectively. The combined mean exclusion chance of these loci for trios and duos is 0.999999 and 0.999747, respectively. Multiple methods like principal component analysis, Fst genetic distance, and phylogenetic reconstruction were employed for dissecting the genetic structure of the Guizhou Han population by comparing it with previously reported populations. As expected, the studied Han population displayed relatively close genetic affinities with the East Asian populations. At the same time, there were obvious genetic differentiations between the Guizhou Han population and other continental populations that were discerned, especially for the African populations. Conclusions This study further verified the applicability of 38 X-InDels for human personal identification and kinship analyses of Han Chinese, and also showed the application potential of X-InDels in population genetics.
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Affiliation(s)
- Yuhang Feng
- Shanghai Key Lab of Forensic Medicine, Key Lab of Forensic Science, Ministry of Justice, China, Academy of Forensic Science, Shanghai, China.,Department of Forensic Medicine, Guizhou Medical University, Guiyang, China
| | - Ting Wang
- Department of Forensic Medicine, Guizhou Medical University, Guiyang, China
| | - Yunteng Yang
- Department of Forensic Medicine, Guizhou Medical University, Guiyang, China
| | - Jiangtao You
- Department of Forensic Medicine, Guizhou Medical University, Guiyang, China
| | - Kun He
- Department of Forensic Medicine, Guizhou Medical University, Guiyang, China
| | - Hongling Zhang
- Department of Forensic Medicine, Guizhou Medical University, Guiyang, China
| | - Qiyan Wang
- Department of Forensic Medicine, Guizhou Medical University, Guiyang, China
| | - Meiqing Yang
- Department of Forensic Medicine, Guizhou Medical University, Guiyang, China
| | - Jiang Huang
- Department of Forensic Medicine, Guizhou Medical University, Guiyang, China
| | - Zheng Ren
- Department of Forensic Medicine, Guizhou Medical University, Guiyang, China
| | - Xiaoye Jin
- Shanghai Key Lab of Forensic Medicine, Key Lab of Forensic Science, Ministry of Justice, China, Academy of Forensic Science, Shanghai, China.,Department of Forensic Medicine, Guizhou Medical University, Guiyang, China
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Mandape SN, Kapema KB, Duque T, Smuts A, King JL, Crysup B, Ge J, Budowle B, Woerner AE. Evaluating probabilistic genotyping for low-pass DNA sequencing. FORENSIC SCIENCE INTERNATIONAL GENETICS SUPPLEMENT SERIES 2022. [DOI: 10.1016/j.fsigss.2022.10.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
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