Institute for Advanced Biosciences

IntroductionRacial and ethnic differences in fetal growth and birth size in the USA have not been adequately explained by individual-level socioeconomic status (SES) factors. We explored whether differences may be partially explained by county-level indicators of SES.MethodsWe linked participant zip codes from the National Institute of Child Health and Human Development Fetal Growth Studies (2009–2013; n=1614) to county-level US census data to calculate a neighbourhood deprivation index, education isolation index and two indices of segregation: racial isolation and evenness. Using causal mediation methods, we evaluated the extent to which racial/ethnic differences in neonatal anthropometrics could be eliminated in a hypothetical setting where everyone lived in counties with high resource availability and racial/ethnic integration.ResultsSetting racial evenness to levels consistent with the highest diversity eliminated 79.9% of the difference in birth weight between non-Hispanic White and non-Hispanic Black and all the difference (106.3%) in birth weight between Hispanic and non-Hispanic White individuals. Setting racial evenness, racial isolation and education isolation to levels consistent with higher diversity and education was also associated with similar reductions in differences for other anthropometric measures.ConclusionsOur findings suggest that, in a hypothetical scenario where everyone lived in counties with low deprivation or segregation, race/ethnic differences in neonatal anthropometry may substantially decrease or be eliminated. Our results also highlight the importance of considering community-level and structural factors in analyses of race/ethnic health disparities.

BackgroundSmall RNAs interacting with PIWI (piRNAs) play a crucial role in regulating transposable elements and translation during spermatogenesis and are essential in male germ cell development. Disruptions in the piRNA pathway typically lead to severe spermatogenic defects and thus male infertility. The HENMT1 gene is a key player in piRNAs primary biogenesis and dysfunction of HENMT1 protein in meiotic and haploid germ cells resulted in the loss of piRNA methylation, piRNA instability, and TE de‐repression. Henmt1‐knockout mice exhibit a severe oligo‐astheno‐teratozoospermia (OAT) phenotype, whereas patients with HENMT1 variants display more severe azoospermia phenotypes, ranging from meiotic arrest to hypospermatogenesis. Through whole‐exome sequencing (WES) of infertile patient cohorts, we identified two new patients with variants in the HENMT1 gene presenting spermatozoa in their ejcaulate, providing us the opportunity to study spermatozoa from these patients.ObjectivesInvestigate the spermatozoa of two patients harboring an HENMT1 variant to determine whether or not these scarce spermatozoa could be used with assisted reproductive technologies.Materials and methodsHENMT1 variants identified by WES were validated through Sanger sequencing. Comprehensive semen analysis was conducted, and sperm cells were subjected to transmission electron microscopy for structural examination, in situ hybridization for aneuploidy assessment, and aniline blue staining for DNA compaction status. Subsequently, we assessed their suitability for in vitro fertilization using intracytoplasmic sperm injection (IVF‐ICSI).ResultsOur investigations revealed a severe OAT phenotype similar to knockout mice, revealing altered sperm concentration, mobility, morphology, aneuploidy and nuclear compaction defects. Multiple IVF‐ICSI attempts were also performed, but no live births were achieved.DiscussionWe confirm the crucial role of HENMT1 in spermatogenesis and highlight a phenotypic continuum associated with HENMT1 variants. Unfortunately, the clinical outcome of these genetic predispositions remains unfavorable, regardless of the patient's phenotype.ConclusionThe presence of spermatozoa is insufficient to anticipate ICSI pregnancy success in HENMT1 patients.

Abstract Background. MYC-driven lymphomas are a subset of B-cell lymphomas characterized by genetic alterations that dysregulate the expression of the MYC oncogene. When overexpressed, typically through chromosomal translocations, amplifications, or other mechanisms, MYC can drive uncontrolled cell growth and contribute to cancer development. MYC-driven lymphomas are described as aggressive entities which require intensive treatment approaches and can be associated with poor prognosis. In the absence of direct MYC-targeting therapy, epigenetic drugs called BET inhibitors (BETi), were shown to reduce MYC levels by disrupting BRD4-dependent transcription associated with the expression of MYC, as well as other oncogenes. Here, we used BETi as molecular tools to better understand oncogenic dependencies in a panel of cell line models of MYC-driven B-cell lymphoma selected to represent their genetic heterogeneity. Results. We first showed that, in these models, MYC expression level does not strictly correlate to the presence of gene alterations. Our data also demonstrated that BETi induces similar growth arrest in all lymphoma cell lines independently of MYC mutational status or expression level. In contrast, BETi-induced cell death was only observed in two cell lines presenting the highest level of MYC protein. This suggest that some MYC-driven lymphoma could present a stronger dependency on MYC for their survival which cannot be predicted on the sole basis on their genetics. This hypothesis was confirmed by gene invalidation experiments, which showed that MYC loss recapitulates the effect on BETi treatment on both cell proliferation and survival, confirming MYC oncogene addiction in these specific models. In contrast, the growth arrest observed in cell lines resistant to BETi-induced apoptosis is not mediated through MYC, but rather through alternative pro-proliferative or oncogenic pathways. Gene expression profiling revealed the basal activation of a specific non-canonical Wnt/Hippo pathway in cell death-resistant cell lines that could be targeted in combination therapy to restore BETi cytotoxicity. Conclusion. This work brings new insights into the complexity of MYC dependencies and unravels a novel targetable oncogenic pathway in aggressive B-cell lymphomas.

Methylmercury (MeHg), a potent neurotoxin, poses substantial risks to prenatal brain development by crossing the placental barrier. In our daily lives, we are exposed to various environmental metals simultaneously with MeHg. Therefore, the combined exposure effects of these metals and MeHg should be investigated. Hence, this study examined the combined fetal exposure effects of MeHg and copper (Cu), an essential element. Gene expression changes in the fetal brains of mice exposed to MeHg, Cu, or both were examined through RNA-seq analysis. Our results showed that the number of variable genes exposed to combined MeHg and Cu increased compared with that in single exposure. Most of them were gene variations specific to combined exposure. Gene Ontology biological process analysis revealed the amplified effects on GABAergic interneurons in the cerebral cortex under combined exposure. IPA pathway analysis indicated considerable variations in pathways related to oxidative stress, neuronal development, and energy metabolism, including the activation of NRF2-mediated oxidative stress response and the suppression of mitochondrial fatty acid beta-oxidation. These findings highlighted the complexity and enhanced risks of combined MeHg and Cu exposure. Therefore, neurodevelopmental effects were more severe and multifaceted than those caused by individual exposures. This research highlighted the importance of understanding the mechanisms of the combined exposure effects of MeHg.

Protein expression varies between cells, and observing this heterogeneity helps to understand biological phenomena. We have developed a water droplet-in-oil digestion (WinO) method for single-cell proteomics. The WinO method reduces adsorption losses of proteins and peptides during sample preparation and allows parallel sample preparation in 96-well plates. However, the original WinO method requires liquid-liquid extraction during the peptide desalting step and manual sample combining after tandem mass tag labeling, which are major obstacles to automating sample preparation. The purpose of the present study was to improve the throughput of the WinO method. First, to eliminate the liquid-liquid extraction step, we used a polystyrene-divinylbenzene reversed-phase sulfonated disk for peptide desalting instead of a polystyrene-divinylbenzene reversed-phase disk. In addition, we changed the organic solvent used from highly volatile ethyl acetate to less volatile hexadecane to improve ease of use. We also used a liquid handling robot for sample combining. With this modified WinO method, the sample preparation time was reduced by three quarters, while the recovery rate remained the same as the original method. This modified WinO method enables automation of the sample preparation process and is expected to be applied to large-scale single-cell proteomics.

How to achieve sustainable food production while reducing environmental impacts is a major concern in agricultural science, and advanced breeding techniques are promising for achieving such goals. However, rice is usually grown under field conditions and influenced by surrounding ecological community members. How ecological communities influence the rice performance in the field has been underexplored despite the potential of ecological communities to establish an environment-friendly agricultural system. In the present study, we demonstrate an ecological-network-based approach to detect potentially influential, previously overlooked organisms for rice (Oryza sativa). First, we established small experimental rice plots, and measured rice growth and monitored ecological community dynamics intensively and extensively using quantitative environmental DNA metabarcoding in 2017 in Japan. We detected more than 1000 species (including microbes and macrobes such as insects) in the rice plots, and nonlinear time series analysis detected 52 potentially influential organisms with lower-level taxonomic information. The results of the time series analysis were validated under field conditions in 2019 by field manipulation experiments. In 2019, we focused on two species, Globisporangium nunn and Chironomus kiiensis, whose abundance was manipulated in artificial rice plots. The responses of rice, namely, the growth rate and gene expression patterns, were measured before and after the manipulation. We confirmed that, especially in the G. nunn-added treatment, rice growth rate and gene expression pattern were changed. In the present study, we demonstrated that intensive monitoring of an agricultural system and the application of nonlinear time series analysis were helpful to identify influential organisms under field conditions. Although the effects of the manipulations were relatively small, the research framework presented here has future potential to harness the ecological complexity and utilize it in agriculture. Our proof-of-concept study would be an important basis for the further development of field-basis system management.

How to achieve sustainable food production while reducing environmental impacts is a major concern in agricultural science, and advanced breeding techniques are promising for achieving such goals. However, rice is usually grown under field conditions and influenced by surrounding ecological community members. How ecological communities influence the rice performance in the field has been underexplored despite the potential of ecological communities to establish an environment-friendly agricultural system. In the present study, we demonstrate an ecological-network-based approach to detect potentially influential, previously overlooked organisms for rice (Oryza sativa). First, we established small experimental rice plots, and measured rice growth and monitored ecological community dynamics intensively and extensively using quantitative environmental DNA metabarcoding in 2017 in Japan. We detected more than 1000 species (including microbes and macrobes such as insects) in the rice plots, and nonlinear time series analysis detected 52 potentially influential organisms with lower-level taxonomic information. The results of the time series analysis were validated under field conditions in 2019 by field manipulation experiments. In 2019, we focused on two species, Globisporangium nunn and Chironomus kiiensis, whose abundance was manipulated in artificial rice plots. The responses of rice, namely, the growth rate and gene expression patterns, were measured before and after the manipulation. We confirmed that, especially in the G. nunn-added treatment, rice growth rate and gene expression pattern were changed. In the present study, we demonstrated that intensive monitoring of an agricultural system and the application of nonlinear time series analysis were helpful to identify influential organisms under field conditions. Although the effects of the manipulations were relatively small, the research framework presented here has future potential to harness the ecological complexity and utilize it in agriculture. Our proof-of-concept study would be an important basis for the further development of field-basis system management.

BackgroundAngiostrongylus cantonensis (rat lungworm) is the main pathogen responsible for eosinophilic meningitis in humans. One of its intermediate snail hosts, Achatina fulica, was already present in many countries around the world before it appeared in the West Indies in the late 1980s. In the French territories in the Caribbean and northern South America, the first cases of human neuroangiostrongyliasis were reported in Martinique, Guadeloupe and French Guiana in 2002, 2013 and 2017, respectively. In order to better characterize angiostrongyliasis in Guadeloupe, particularly its geographical origin and route of introduction, we undertook molecular characterization of adult worms of Angiostrongylus cantonensis and its intermediate host Achatina fulica.MethodsGenomic DNA of adult Angiostrongylus cantonensis and Achatina fulica was extracted and amplified by polymerase chain reaction (PCR) targeting the mitochondrial genes cytochrome B and C for A. cantonensis and 16S ribosomal RNA for A. fulica. The PCR products were sequenced and studied by phylogenetic analysis.ResultsCytochrome B and cytochrome C molecular markers indicate a monophyletic lineage of A. cantonensis adult worms in Guadeloupe. Two sequences of A. fulica were identified.ConclusionsThese results confirm the recent introduction of both Angiostrongylus cantonensis and Achatina fulica into Guadeloupe. Achatina fulica in Guadeloupe shares a common origin with those in Barbados and New Caledonia, while Angiostrongylus cantonensis in Guadeloupe shares a common origin with those in Brazil, Hawaii and Japan.Graphical

Saturated fatty acids (SFAs) during pregnancy are associated with disrupted metabolic programming among offspring at birth and later growth. We examined plasma phospholipid SFAs in early pregnancy and fetal growth throughout pregnancy. We enrolled 321 pregnant women from the NICHD Fetal Growth Studies-Singleton Cohort at gestational weeks 8-13. Ultrasonogram schedules were randomly assigned to capture weekly fetal growth. We measured plasma phospholipid SFAs at early pregnancy using blood samples and modeled fetal growth trajectories across tertiles of SFAs with cubic splines using linear mixed models after full adjustment. We then compared pairwise weekly fetal growth biometrics referencing the lowest tertile in each SFA using the Wald test. We found that even-chain and very long even-chain SFAs were inversely associated, whereas odd-chain SFAs were positively associated with fetal weight and size. Compared with the lowest tertile, the highest tertile of pentadecanoic acid (15:0) had a greater fetal weight and size, starting from week 13 until late pregnancy (at week 39: 3429.89 vs. 3269.08 g for estimated fetal weight; 328.14 vs. 323.00 mm for head circumference). Our findings could inspire future interventions using an alternative high-fat diet rich in odd-chain SFAs for optimal fetal growth.