Point mutation revealed the resurgence of sub-genotype VII.2 Newcastle disease virus in Israel.

RESEARCH HIGHLIGHTSIn 2019, there was a resurgence of NDV from sub-genotype VII.2 in Israel, in an already endemic area of sub-genotype VII.1.A mismatch at the 3' end of the reverse primer caused a diagnostic failure of the NDV virulence differentiation rRT-PCR assay.The 2019 NDV sub-genotype VII.2 virus is genetically close to viruses from Jordan (2018) and Pakistan (2015-2016).

Molecular epidemiology of hepatitis B virus mutants associated with vaccine escape, drug resistance and diagnosis failure.

The massive implementation of the vaccine and antiviral agents against hepatitis B virus (HBV), targeting the envelope and viral polymerase genes, induces a selection pressure that might lead to the emergence of variants that impair the effectiveness of the vaccine, diagnostic methods and antiviral therapy. The aim of this study was to evaluate the prevalence of HBV vaccine escape mutants (VEMs), diagnostic failure mutants (DFMs) and treatment resistance mutants (ARMs) among individuals from Buenos Aires, Argentina. HBV surface antigen and polymerase sequences obtained from serum samples of 530 HBV-infected individuals were analysed. Samples belonged to genotypes A (28.1%), D (13.6%) and F (58.3%). VEMs, DMFs and ARMs were present in 40 (7.5%), 57 (10.7%) and 27 (5.1%) samples within the studied population. Additionally, eight nonpreviously reported VEMs and nine DFMs were identified. VEMs and DFMs were biased by genotype, being higher in genotype D (33.3% and 33.3%) compared to genotype A (6% and 17.4%) and genotype F (2.3% and 2.3%) (P > 0.001). On the contrary, there was no association between the presence of ARMs and HBV genotype (P = 0.324). VEMs, DFMs and ARMs create public health concerns. The current study provided valuable information about mutants in surface antigen and polymerase in HBV-infected patients from Argentina where HBV-F is the most prevalent genotype. Consequently, it constitutes an important reference for Latin American clinicians in order to optimize the management of HBV-infected patients.

Targeted Sanger sequencing to recover key mutations in SARS-CoV-2 variant genome assemblies produced by next-generation sequencing.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is adaptively evolving to ensure its persistence within human hosts. It is therefore necessary to continuously monitor the emergence and prevalence of novel variants that arise. Importantly, some mutations have been associated with both molecular diagnostic failures and reduced or abrogated next-generation sequencing (NGS) read coverage in some genomic regions. Such impacts are particularly problematic when they occur in genomic regions such as those that encode the spike (S) protein, which are crucial for identifying and tracking the prevalence and dissemination dynamics of concerning viral variants. Targeted Sanger sequencing presents a fast and cost-effective means to accurately extend the coverage of whole-genome sequences. We designed a custom set of primers to amplify a 401 bp segment of the receptor-binding domain (RBD) (between positions 22698 and 23098 relative to the Wuhan-Hu-1 reference). We then designed a Sanger sequencing wet-laboratory protocol. We applied the primer set and wet-laboratory protocol to sequence 222 samples that were missing positions with key mutations K417N, E484K, and N501Y due to poor coverage after NGS sequencing. Finally, we developed SeqPatcher, a Python-based computational tool to analyse the trace files yielded by Sanger sequencing to generate consensus sequences, or take preanalysed consensus sequences in fasta format, and merge them with their corresponding whole-genome assemblies. We successfully sequenced 153 samples of 222 (69 %) using Sanger sequencing and confirmed the occurrence of key beta variant mutations (K417N, E484K, N501Y) in the S genes of 142 of 153 (93 %) samples. Additionally, one sample had the Y508F mutation and four samples the S477N. Samples with RT-PCR Ct scores ranging from 13.85 to 37.47 (mean=25.70) could be Sanger sequenced efficiently. These results show that our method and pipeline can be used to improve the quality of whole-genome assemblies produced using NGS and can be used with any pairs of the most used NGS and Sanger sequencing platforms.

A Cognitive Autopsy Approach Towards Explaining Diagnostic Failure.

Diagnostic failure has emerged as one of the most significant threats to patient safety. It is important to understand the antecedents of such failures both for clinicians in practice as well is those in training. A consensus has developed in the literature that the majority of failures are due to individual or system factors or some combination of the two. A major source of variance in individual clinical performance is cognitive and affective biases; however, their role in clinical decision making has been difficult to assess partly because they are difficult to investigate experimentally. A significant drawback has been that experimental manipulations appear to confound the assessment of the context surrounding the diagnostic process itself. We conducted an exercise on selected actual cases of diagnostic errors to explore the effect of biases in the 'real world' emergency medicine (EM) context. Thirty anonymized EM cases were analysed in depth through a process of root cause analysis that included an assessment of error-producing conditions (EPCs), knowledge-based errors, and how clinicians were thinking and deciding during each case. A prominent feature of the exercise was the identification of the occurrence of and interaction between specific cognitive and affective biases, through a process called cognitive autopsy. The cases covered a broad range of diagnoses across a wide variety of disciplines. A total of 24 discrete cognitive and affective biases that contributed to misdiagnosis were identified and their incidence recorded. Five to six biases were detected per case, and observed on 168 occasions across the 30 cases. Thirteen EPCs were identified. Knowledge-based errors were rare, occurring in only five definite instances. The ordinal position in which biases appeared in the diagnostic process was recorded. This experiment provides a baseline for investigating and understanding the critical role that biases play in clinical decision making as well as providing a credible explanation for why diagnoses fail.