Dependency of mitochondrial quantity on blastocyst timeline obscures its actual effect to pregnancy outcomes.

Objectives: To explore the correlation between mitochondrial quantity and the blastocyst development timeline as well as their respective contributions to early pregnancy. Methods: A retrospective study was conducted using a dataset comprising 2,633 embryos that underwent preimplantation genetic testing for aneuploidy (PGT-A) between January 2016 and December 2023. The study was divided into three subsets to address distinct aspects: the representativeness of a single trophectoderm (TE) biopsy for mitochondrial quantity (n=43), the correlation between morphokinetic features and mitochondrial quantity (n=307), and the association analysis among mitochondrial quantity, blastocyst timeline factor, and reproductive outcomes (n=2,283). Distribution assessment of mitochondrial quantity across an individual blastocyst involved the identification within multiple biopsies and spent culture media. Timeline evaluation included correlating mitochondrial quantity with time-lapse datasets. Finally, multivariate logistic regression models, incorporating potential effectors alongside mitochondrial quantity, were employed to analyze their respective contributions to early pregnancy endpoints. Results: Of distribution assessment, mitochondrial quantity exhibited an even distribution across the entire trophectoderm (Spearman's ρ=0.82), while no detectable mtDNAs in the corresponding spent culture media. Then the timeline correlation study revealed significant association between mitochondrial quantity and blastocyst features of both the day of expanded blastocyst formation (95% Confidence intervals, CIs: 0.27~4.89, p=0.03) and the timing of expanded blastocyst formation (tEB) (95% CIs: -0.24~-0.01, p=0.04) in the regression model, indicating a strong dependency between mitochondrial quantity and the blastocyst development timeline. For the contribution to early pregnancy, multivariate logistic regression models showed that the day of expanded blastocyst formation contributed to four endpoints persistently: positive for HCG (odd ratio, OR: 0.71, p=0.006), gestational sac (OR: 0.78, p=0.04), fetal heartbeat (OR: 0.71, p=0.004), and progression to 14 weeks (OR: 0.69, p=0.002). Contrastingly, no notable correlation was observed between the mitochondrial quantity and these endpoints. Conclusions: Strong interaction was observed between mitochondrial quantity and the blastocyst timeline, particularly the timing of expanded blastocyst formation. It suggests that the primary determinant influencing pregnancy outcomes lies in the time-dependent parameter of blastocyst rather than in the specific mitochondrial quantity.

Reduced mitochondrial DNA content correlate with poor clinical outcomes in cryotransfers with day 6 single euploid embryos.

Objective: To investigate whether the mitochondrial DNA (mtDNA) content of a single biopsy at trophoblast correlates with the developmental potential and reproductive outcomes of blastocyst. Methods: A retrospective analysis applied the dataset of 1,675 embryos with preimplantation genetic testing for aneuploidy (PGT-A) from 1,305 individuals, and 1,383 embryos involved cryotransfers of single euploid embryo between January 2015 and December 2019. The studied cohort was divided for algorithm establishment on the NGS platform (n=40), correlation of biological features (n=1,635), and correlation of reproductive outcomes (n=1,340). Of the algorithm derived from the NGS platform, the reliability and repeatability were validated via qPCR assay and inter-run controls, respectively. Of the correlation across biological features, stratification analyses were applied to evaluate the effect from a single contributor. Eventually, the correlation between the mtDNA ratios and reproductive outcomes was adjusted according to the significant effector(s). Results: The mtDNA ratios showed statistically different between embryos with different days of blastocyst formation ([Day 5]: 1.06 vs. [Day 6]: 0.66, p=0.021), and between embryos with different expansion stages ([Expansion 5]: 1.05 vs. [Expansion 6]: 0.49, p=0.012). None or weakly correlated with the maternal age, morphology, ploidy, and gender. Analyzed by the different days of blastocyst formation with fixed expansion score as 5 in the euploid single embryo transfers (eSET), the day 6 eSET showed significantly lower reduced mtDNA ratio (n=139) in failure groups of fetal heartbeat (p=0.004), ongoing pregnancy (p=0.007), and live birth (p=0.01); however, no correlation between mtDNA ratios and pregnancy outcomes was observed in the day 5 eSET (n=1,201). Conclusions: The study first demonstrated that mtDNA ratio was dependent on the days of blastocyst formation while expansion stage was fixed. Lower mtDNA ratios were observed in the day 6 eSET with adverse outcomes. The present stratification analyses reveal that the timeline of embryo is an important covariate to the mtDNA content.

High concordance in preimplantation genetic testing for aneuploidy between automatic identification via Ion S5 and manual identification via Miseq.

The Ion S5 (Thermo Fisher Scientific) and Miseq (Illumina) NGS systems are both widely used in the clinical laboratories conducting PGT-A. Each system employs discrepant library preparation steps, sequencing principles, and data processing algorithms. The automatic interpretation via Ion Reporter software (Thermo Fisher Scientific) and the manual interpretation via BlueFuse Multi software (Illumina) for chromosomal copy number variation (CNV) represent very different reporting approaches. Thus, it is intriguing to compare their ability of ploidy detection as PGT-A/NGS system. In the present study, four aneuploid cell lines were individually mixed with a diploid cell line at different aneuploid ratios of 0% (0:5), 10% (1:9), 20% (1:4), 40% (2:3), 50% (3:3), 60% (3:2), 80% (4:1) and 100% (5:0) to assess the sensitivity and specificity for whole chromosomal and segmental aneuploidy detection. The clinical biopsies of 107 blastocysts from 46 IVF/PGT-A cycles recruited between December 2019 and February 2020 were used to calculate the concordance. Initially, the pre-amplified products were divided into two aliquots for different library preparation procedures of each system. Applying the same calling criteria, automatic identification was achieved through the Ion Reporter, while well-trained technicians manually identified each sample through the BlueFuse Multi. The results displayed that both systems reliably distinguished chromosomal CNV of the mixtures with at least 10% aneuploidy from karyotypically normal samples ([Ion S5] whole-chromosomal duplication: 2.14 vs. 2.05, p value = 0.009, segmental deletion: 1.88 vs. 2.05, p value = 0.003; [Miseq] whole-chromosomal duplication: 2.12 vs. 2.03, p value = 0.047, segmental deletion: 1.82 vs. 2.03, p value = 0.002). The sensitivity and specificity were comparable between the Ion S5 and Miseq ([sensitivity] 93% vs. 90%, p = 0.78; [specificity] 100% vs. 100%, p value = 1.0). In the 107 clinical biopsies, three displayed chaotic patterns (2.8%), which could not be interpreted for the ploidy. The ploidy concordance was 99.04% (103/104) per embryo and 99.47% (2265/2277) per chromosome pair. Since their ability of detection were proven to be similar, the automatic identification in Ion S5 system presents comparatively faster and more standardized performance.

Metagenome and Metatranscriptome Profiling of Moderate and Severe COPD Sputum in Taiwanese Han Males.

Chronic obstructive pulmonary disease (COPD) is an inflammatory lung disorder characterized by the progressive obstruction of airflow and is currently the fourth leading cause of death in the world. The pathogenesis of COPD is thought to involve bacterial infections and inflammations. Owing to advancement in sequencing technology, evidence is emerging that supports an association between the lung microbiome and COPD. However, few studies have looked into the expression profile of the bacterial communities in the COPD lungs. In this study, we analyzed the sputum microbiome of four moderate and four severe COPD male patients both at the DNA and RNA level, using next generation sequencing technology. We found that bacterial composition determined by 16S rRNA gene sequencing may not directly translate to the set of actively expressing bacteria as defined by transcriptome sequencing. The two sequencing data agreed on Prevotella, Rothia, Neisseria, Porphyromonas, Veillonella, Fusobacterium and Streptococcus being among the most differentially abundant genera between the moderate and severe COPD samples, supporting their association with COPD severity. However, the two sequencing analyses disagreed on the relative abundance of these bacteria in the two COPD groups, implicating the importance of studying the actively expressing bacteria for enriching our understanding of COPD. Though we have described the metatranscriptome profiles of the lung microbiome in moderate and severe COPD, further investigations are required to determine the functional basis underlying the relationship between the microbial species in the lungs and pathogenesis of COPD.