Molecular characterization of Mycoplasma pneumoniae infections in Moscow from 2015 to 2018

The aim of this study was to assess which Mycoplasma pneumoniae genotypes were present in Moscow during the years 2015-2018 and whether the proportion between detected genotypes changed over time. We were also interested in the presence of macrolide resistance (MR)Mycoplasma pneumoniae. We performed multilocus variable-number tandem-repeat (VNTR) analysis (MLVA), SNP typing, and mutation typing in the 23S rRNA gene from 117 M. pneumoniae clinical isolates. Our analysis suggests two major MLVA types: 4572 and 3562. In 2017-2018, MLVA type 4572 gradually became predominant. In general, the SNP type range is the same as described earlier for European countries. The analysis of MR mutations showed that 7% of the isolates had an A2063G mutation in the 23S rRNA gene with no isolates carrying an A2064G mutation. In 2017-2018, MLVA type 4572 (SNP type 1) begins to spread in Moscow, which was widespread globally, especially in Asian countries. SNP typing of our sample showed higher discriminatory power than MLVA typing.

Prospective Study of a Cohort of Russian Nijmegen Breakage Syndrome Patients Demonstrating Predictive Value of Low Kappa-Deleting Recombination Excision Circle (KREC) Numbers and Beneficial Effect of Hematopoietic Stem Cell Transplantation (HSCT)

BACKGROUND

Nijmegen breakage syndrome (NBS) is a combined primary immunodeficiency with DNA repair defect, microcephaly, and other phenotypical features. It predominantly occurs in Slavic populations that have a high frequency of carriers with the causative NBN gene c.657_661del5 mutation. Due to the rarity of the disease in the rest of the world, studies of NBS patients are few. Here, we report a prospective study of a cohort of Russian NBS patients.

METHODS

35 Russian NBS patients of ages 1-19 years, referred to our Center between years 2012 and 2016, were prospectively studied.

RESULTS

Despite the fact that in 80% of the patients microcephaly was diagnosed at birth or shortly thereafter, the average delay of NBS diagnosis was 6.5 years. Though 80% of the patients had laboratory signs of immunodeficiency, only 51% of the patients experienced significant infections. Autoimmune complications including interstitial lymphocytic lung disease and skin granulomas were noted in 34%, malignancies-in 57% of the patients. T-cell excision circle (TREC)/kappa-deleting recombination excision circle (KREC) levels were low in the majority of patients studied. Lower KREC levels correlated with autoimmune and oncological complications. Fifteen patients underwent hematopoietic stem cell transplantation (HSCT), 10 of them were alive and well, with good graft function. Three patients in the HSCT group and five non-transplanted patients died; tumor progression being the main cause of death. The probability of the overall survival since NBS diagnosis was 0.76 in the HSCT group and 0.3 in the non-transplanted group.

CONCLUSION

Based on our findings of low TRECs in most NBS patients, independent of their age, TREC detection can be potentially useful for detection of NBS patients during neonatal screening. KREC concentration can be used as a prognostic marker of disease severity. HSCT is a viable treatment option in NBS and should be especially considered in patients with low KREC numbers early on, before development of life-threatening complications.

Base-calling algorithm with vocabulary (BCV) method for analyzing population sequencing chromatograms

Sanger sequencing is a common method of reading DNA sequences. It is less expensive than high-throughput methods, and it is appropriate for numerous applications including molecular diagnostics. However, sequencing mixtures of similar DNA of pathogens with this method is challenging. This is important because most clinical samples contain such mixtures, rather than pure single strains. The traditional solution is to sequence selected clones of PCR products, a complicated, time-consuming, and expensive procedure. Here, we propose the base-calling with vocabulary (BCV) method that computationally deciphers Sanger chromatograms obtained from mixed DNA samples. The inputs to the BCV algorithm are a chromatogram and a dictionary of sequences that are similar to those we expect to obtain. We apply the base-calling function on a test dataset of chromatograms without ambiguous positions, as well as one with 3-14% sequence degeneracy. Furthermore, we use BCV to assemble a consensus sequence for an HIV genome fragment in a sample containing a mixture of viral DNA variants and to determine the positions of the indels. Finally, we detect drug-resistant Mycobacterium tuberculosis strains carrying frameshift mutations mixed with wild-type bacteria in the pncA gene, and roughly characterize bacterial communities in clinical samples by direct 16S rRNA sequencing.