Deep-learning-based multi-class segmentation for automated, non-invasive routine assessment of human pluripotent stem cell culture status.

Human induced pluripotent stem cells (hiPSCs) are capable of differentiating into a variety of human tissue cells. They offer new opportunities for personalized medicine and drug screening. This requires large quantities of high quality hiPSCs, obtainable only via automated cultivation. One of the major requirements of an automated cultivation is a regular, non-invasive analysis of the cell condition, e.g. by whole-well microscopy. However, despite the urgency of this requirement, there are currently no automatic, image-processing-based solutions for multi-class routine quantification of this nature. This paper describes a method to fully automate the cell state recognition based on phase contrast microscopy and deep-learning. This approach can be used for in process control during an automated hiPSC cultivation. The U-Net based algorithm is capable of segmenting important parameters of hiPSC colony formation and can discriminate between the classes hiPSC colony, single cells, differentiated cells and dead cells. The model achieves more accurate results for the classes hiPSC colonies, differentiated cells, single hiPSCs and dead cells than visual estimation by a skilled expert. Furthermore, parameters for each hiPSC colony are derived directly from the classification result such as roundness, size, center of gravity and inclusions of other cells. These parameters provide localized information about the cell state and enable well based treatment of the cell culture in automated processes. Thus, the model can be exploited for routine, non-invasive image analysis during an automated hiPSC cultivation. This facilitates the generation of high quality hiPSC derived products for biomedical purposes.

The StemCellFactory: A Modular System Integration for Automated Generation and Expansion of Human Induced Pluripotent Stem Cells.

While human induced pluripotent stem cells (hiPSCs) provide novel prospects for disease-modeling, the high phenotypic variability seen across different lines demands usage of large hiPSC cohorts to decipher the impact of individual genetic variants. Thus, a much higher grade of parallelization, and throughput in the production of hiPSCs is needed, which can only be achieved by implementing automated solutions for cell reprogramming, and hiPSC expansion. Here, we describe the StemCellFactory, an automated, modular platform covering the entire process of hiPSC production, ranging from adult human fibroblast expansion, Sendai virus-based reprogramming to automated isolation, and parallel expansion of hiPSC clones. We have developed a feeder-free, Sendai virus-mediated reprogramming protocol suitable for cell culture processing via a robotic liquid handling unit that delivers footprint-free hiPSCs within 3 weeks with state-of-the-art efficiencies. Evolving hiPSC colonies are automatically detected, harvested, and clonally propagated in 24-well plates. In order to ensure high fidelity performance, we have implemented a high-speed microscope for in-process quality control, and image-based confluence measurements for automated dilution ratio calculation. This confluence-based splitting approach enables parallel, and individual expansion of hiPSCs in 24-well plates or scale-up in 6-well plates across at least 10 passages. Automatically expanded hiPSCs exhibit normal growth characteristics, and show sustained expression of the pluripotency associated stem cell marker TRA-1-60 over at least 5 weeks (10 passages). Our set-up enables automated, user-independent expansion of hiPSCs under fully defined conditions, and could be exploited to generate a large number of hiPSC lines for disease modeling, and drug screening at industrial scale, and quality.

The DAOA/G30 locus and affective disorders: haplotype based association study in a polydiagnostic approach.

BACKGROUND: The DAOA/G30 (D-amino acid oxidase activator) gene complex at chromosomal region 13q32-33 is one of the most intriguing susceptibility loci for the major psychiatric disorders, although there is no consensus about the specific risk alleles or haplotypes across studies. METHODS: In a case-control sample of German descent (affective psychosis: n = 248; controls: n = 188) we examined seven single nucleotide polymorphisms (SNPs) around DAOA/G30 (rs3916966, rs1935058, rs2391191, rs1935062, rs947267, rs3918342, and rs9558575) for genetic association in a polydiagnostic approach (ICD 10; Leonhard's classification). RESULTS: No single marker showed evidence of overall association with affective disorder neither in ICD10 nor Leonhard's classification. Haplotype analysis revealed no association with recurrent unipolar depression or bipolar disorder according to ICD10, within Leonhard's classification manic-depression was associated with a 3-locus haplotype (rs2391191, rs1935062, and rs3916966; P = 0.022) and monopolar depression with a 5-locus combination at the DAOA/G30 core region (P = 0.036). CONCLUSION: Our data revealed potential evidence for partially overlapping risk haplotypes at the DAOA/G30 locus in Leonhard's affective psychoses, but do not support a common genetic contribution of the DAOA/G30 gene complex to the pathogenesis of affective disorders.

Is FKBP5 a genetic marker of affective psychosis? A case control study and analysis of disease related traits.

BACKGROUND: A dysregulation of the hypothalamic-pituitary-adrenal (HPA) axis has been proposed as an important pathogenic factor in depression. Genetic variants of FKBP5, a protein of the HPA system modulating the glucocorticoid receptor, have been reported to be genetically associated with improved response to medical treatment and an increase of depressive episodes. METHODS: We examined three single nucleotide polymorphisms (SNPs) in FKBP5, rs4713916 in the proposed promoter region, rs1360780 in the second intron and rs3800373 in the 3'-untranslated region (3'-UTR), in a case-control study of Caucasian origin (affective psychosis: n = 248; controls: n = 188) for genetic association and association with disease related traits. RESULTS: Allele and genotype frequencies of rs4713916, rs1360780 and rs3800373 were not significantly different between cases and controls. Two three-locus haplotypes, G-C-T and A-T-G, accounted for 86.2% in controls. Odds ratios were not increased between cases and controls, except the rare haplotype G-C-G (OR 6.81), representing 2.1% of cases and 0.3% of controls. The frequency of rs4713916AG in patients deviated from expected Hardy-Weinberg equilibrium, the genotype AA at rs4713916 in monopolar depression (P = 0.011), and the two-locus haplotype rs1360780T--rs3800373T in the total sample (overall P = 0.045) were nominally associated with longer continuance of disease. CONCLUSION: Our data do not support a significant genetic contribution of FKBP5 polymorphisms and haplotypes to affective psychosis, and the findings are inconclusive regarding their contribution to disease-related traits.

ZDHHC8 as a candidate gene for schizophrenia: analysis of a putative functional intronic marker in case-control and family-based association studies.

BACKGROUND: The chromosome 22q11 region is proposed as a major candidate locus for susceptibility genes to schizophrenia. Recently, the gene ZDHHC8 encoding a putative palmitoyltransferase at 22q11 was proposed to increase liability to schizophrenia based on both animal models and human association studies by significant over-transmission of allele rs175174A in female, but not male subjects with schizophrenia. METHODS: Given the genetic complexity of schizophrenia and the potential genetic heterogeneity in different populations, we examined rs175174 in 204 German proband-parent triads and in an independent case-control study (schizophrenic cases: n = 433; controls: n = 186). RESULTS: In the triads heterozygous parents transmitted allele G preferentially to females, and allele A to males (heterogeneity chi2 = 4.43; p = 0.035). The case-control sample provided no further evidence for overall or gender-specific effects regarding allele and genotype frequency distributions. CONCLUSION: The findings on rs175174 at ZDHHC8 are still far from being conclusive, but evidence for sexual dimorphism is moderate, and our data do not support a significant genetic contribution of rs175174 to the aetiopathogenesis of schizophrenia.