Structural analysis of random transgene integration in CHO manufacturing cell lines by targeted sequencing.

Genetically modified CHO cell lines are traditionally used for the production of biopharmaceuticals. However, an in-depth molecular understanding of the mechanism and exact position of transgene integration into the genome of pharmaceutical manufacturing cell lines is still scarce. Next-generation sequencing (NGS) holds great promise for strongly facilitating the understanding of CHO cell factories, as it has matured to a powerful and affordable technology for cellular genotype analysis. Targeted Locus Amplification (TLA) combined with NGS allows for robust detection of genomic positions of transgene integration and structural genomic changes occurring upon stable integration of expression vectors. TLA was applied to generate comparative genomic fingerprints of several CHO production cell lines expressing different monoclonal antibodies. Moreover, high producers resulting from an additional round of transfection of an existing cell line (supertransfection) were analyzed to investigate the integrity and the number of integration sites. Our analyses enabled detailed genetic characterization of the integration regions with respect to the number of integrates and structural changes of the host cell's genome. Single integration sites per clone with concatenated transgene copies could be detected and were in some cases found to be associated with genomic rearrangements, deletions or translocations. Supertransfection resulted in an increase in titer associated with an additional integration site per clone. Based on the TLA fingerprints, CHO cell lines originating from the same mother clone could clearly be distinguished. Interestingly, two CHO cell lines originating from the same mother clone were shown to differ genetically and phenotypically despite their identical TLA fingerprints. Taken together, TLA provides an accurate genetic characterization with respect to transgene integration sites compared with conventional methods and represents a valuable tool for a comprehensive evaluation of CHO production clones early in cell line development.

Microbiome dynamics and adaptation of expression signatures during methane production failure and process recovery.

This study aimed to uncover microbial dynamics and transcriptional adaptations during mesophilic AD of maize silage and slurry. While one digester performed under optimal conditions, the investigations also evaluated the microbiome during a temperature drop mediated process failure accompanied by acidification and how it contributed to a process recovery. Composition and pathway activities were analyzed by whole genome shotgun (WGS) and metatranscriptome sequencing, respectively. A biodiversity of 112 species was observed with noticeable shifts over process time. Although four distinct groups of microbes could be identified with a correlating versatility according to substrate and to process disturbance, also tremendous effects on gene expression were monitored especially of the archaeal methane metabolism. Particularly, the expression of acetogenotrophic methanogenesis related genes was identified to be relevant for process regeneration.

Two routes to senescence revealed by real-time analysis of telomerase-negative single lineages.

In eukaryotes, telomeres cap chromosome ends to maintain genomic stability. Failure to maintain telomeres leads to their progressive erosion and eventually triggers replicative senescence, a pathway that protects against unrestricted cell proliferation. However, the mechanisms underlying the variability and dynamics of this pathway are still elusive. Here we use a microfluidics-based live-cell imaging assay to investigate replicative senescence in individual Saccharomyces cerevisiae cell lineages following telomerase inactivation. We characterize two mechanistically distinct routes to senescence. Most lineages undergo an abrupt and irreversible switch from a replicative to an arrested state, consistent with telomeres reaching a critically short length. In contrast, other lineages experience frequent and stochastic reversible arrests, consistent with the repair of accidental telomere damage by Pol32, a subunit of polymerase δ required for break-induced replication and for post-senescence survival. Thus, at the single-cell level, replicative senescence comprises both deterministic cell fates and chaotic cell division dynamics.

Aging yeast cells undergo a sharp entry into senescence unrelated to the loss of mitochondrial membrane potential.

In budding yeast, a mother cell can produce a finite number of daughter cells before it stops dividing and dies. Such entry into senescence is thought to result from a progressive decline in physiological function, including a loss of mitochondrial membrane potential (ΔΨ). Here, we developed a microfluidic device to monitor the dynamics of cell division and ΔΨ in real time at single-cell resolution. We show that cells do not enter senescence gradually but rather undergo an abrupt transition to a slowly dividing state. Moreover, we demonstrate that the decline in ΔΨ, which is observed only in a fraction of cells, is not responsible for entry into senescence. Rather, the loss of ΔΨ is an age-independent and heritable process that leads to clonal senescence and is therefore incompatible with daughter cell rejuvenation. These results emphasize the importance of quantitative single-cell measurements to decipher the causes of cellular aging.

Natural sequence variants of yeast environmental sensors confer cell-to-cell expression variability.

Living systems may have evolved probabilistic bet hedging strategies that generate cell-to-cell phenotypic diversity in anticipation of environmental catastrophes, as opposed to adaptation via a deterministic response to environmental changes. Evolution of bet hedging assumes that genotypes segregating in natural populations modulate the level of intraclonal diversity, which so far has largely remained hypothetical. Using a fluorescent P(met17)-GFP reporter, we mapped four genetic loci conferring to a wild yeast strain an elevated cell-to-cell variability in the expression of MET17, a gene regulated by the methionine pathway. A frameshift mutation in the Erc1p transmembrane transporter, probably resulting from a release of laboratory strains from negative selection, reduced P(met17)-GFP expression variability. At a second locus, cis-regulatory polymorphisms increased mean expression of the Mup1p methionine permease, causing increased expression variability in trans. These results demonstrate that an expression quantitative trait locus (eQTL) can simultaneously have a deterministic effect in cis and a probabilistic effect in trans. Our observations indicate that the evolution of transmembrane transporter genes can tune intraclonal variation and may therefore be implicated in both reactive and anticipatory strategies of adaptation.

Single-cell phenomics reveals intra-species variation of phenotypic noise in yeast.

BACKGROUND: Most quantitative measures of phenotypic traits represent macroscopic contributions of large numbers of cells. Yet, cells of a tissue do not behave similarly, and molecular studies on several organisms have shown that regulations can be highly stochastic, sometimes generating diversified cellular phenotypes within tissues. Phenotypic noise, defined here as trait variability among isogenic cells of the same type and sharing a common environment, has therefore received a lot of attention. Given the potential fitness advantage provided by phenotypic noise in fluctuating environments, the possibility that it is directly subjected to evolutionary selection is being considered. For selection to act, phenotypic noise must differ between contemporary genotypes. Whether this is the case or not remains, however, unclear because phenotypic noise has very rarely been quantified in natural populations. RESULTS: Using automated image analysis, we describe here the phenotypic diversity of S. cerevisiae morphology at single-cell resolution. We profiled hundreds of quantitative traits in more than 1,000 cells of 37 natural strains, which represent various geographical and ecological origins of the species. We observed abundant trait variation between strains, with no correlation with their ecological origin or population history. Phenotypic noise strongly depended on the strain background. Noise variation was largely trait-specific (specific strains showing elevated noise for subset of traits) but also global (a few strains displaying elevated noise for many unrelated traits). CONCLUSIONS: Our results demonstrate that phenotypic noise does differ quantitatively between natural populations. This supports the possibility that, if noise is adaptive, microevolution may tune it in the wild. This tuning may happen on specific traits or by varying the degree of global phenotypic buffering.

Finding modulators of stochasticity levels by quantitative genetics.

Although bakers and wine makers constantly select, compare, and hunt for new wild strains of Saccharomyces cerevisiae, yeast geneticists have long focused on a few "standard" strains to ensure reproducibility and easiness of experimentation. And so far, the wonderful natural resource of wild genetic variation has been poorly exploited in most academic laboratories. We describe here how one can use this resource to investigate the molecular sources of stochasticity in a gene regulatory network. The approach is general enough to be applied to any network of interest, as long as the experimental read-out offers robust statistics. For a given network, a typical study first identifies two backgrounds A and B displaying different levels of stochasticity and then study the network in A × B progeny. Taking advantage of microarrays or resequencing technologies, genotyping of appropriate segregants can then lead to the genomic regions housing modulators of stochasticity. The powerful toolbox available to manipulate the yeast genome offers several ways to narrow these regions further and to unambiguously demonstrate the regulatory consequences of DNA polymorphisms.

Natural single-nucleosome epi-polymorphisms in yeast.

Epigenomes commonly refer to the sequence of presence/absence of specific epigenetic marks along eukaryotic chromatin. Complete histone-borne epigenomes have now been described at single-nucleosome resolution from various organisms, tissues, developmental stages, or diseases, yet their intra-species natural variation has never been investigated. We describe here that the epigenomic sequence of histone H3 acetylation at Lysine 14 (H3K14ac) differs greatly between two unrelated strains of the yeast Saccharomyces cerevisiae. Using single-nucleosome chromatin immunoprecipitation and mapping, we interrogated 58,694 nucleosomes and found that 5,442 of them differed in their level of H3K14 acetylation, at a false discovery rate (FDR) of 0.0001. These Single Nucleosome Epi-Polymorphisms (SNEPs) were enriched at regulatory sites and conserved non-coding DNA sequences. Surprisingly, higher acetylation in one strain did not imply higher expression of the relevant gene. However, SNEPs were enriched in genes of high transcriptional variability and one SNEP was associated with the strength of gene activation upon stimulation. Our observations suggest a high level of inter-individual epigenomic variation in natural populations, with essential questions on the origin of this diversity and its relevance to gene x environment interactions.

Cell-to-cell stochastic variation in gene expression is a complex genetic trait.

The genetic control of common traits is rarely deterministic, with many genes contributing only to the chance of developing a given phenotype. This incomplete penetrance is poorly understood and is usually attributed to interactions between genes or interactions between genes and environmental conditions. Because many traits such as cancer can emerge from rare events happening in one or very few cells, we speculate an alternative and complementary possibility where some genotypes could facilitate these events by increasing stochastic cell-to-cell variations (or 'noise'). As a very first step towards investigating this possibility, we studied how natural genetic variation influences the level of noise in the expression of a single gene using the yeast S. cerevisiae as a model system. Reproducible differences in noise were observed between divergent genetic backgrounds. We found that noise was highly heritable and placed under a complex genetic control. Scanning the genome, we mapped three Quantitative Trait Loci (QTL) of noise, one locus being explained by an increase in noise when transcriptional elongation was impaired. Our results suggest that the level of stochasticity in particular molecular regulations may differ between multicellular individuals depending on their genotypic background. The complex genetic architecture of noise buffering couples genetic to non-genetic robustness and provides a molecular basis to the probabilistic nature of complex traits.

A biophysical approach to the optimisation of dendritic-tumour cell electrofusion.

Electrofusion of tumour and dendritic cells (DCs) is a promising approach for production of DC-based anti-tumour vaccines. Although human DCs are well characterised immunologically, little is known about their biophysical properties, including dielectric and osmotic parameters, both of which are essential for the development of efficient electrofusion protocols. In the present study, human DCs from the peripheral blood along with a tumour cell line used as a model fusion partner were examined by means of time-resolved cell volumetry and electrorotation. Based on the biophysical cell data, the electrofusion protocol could be rapidly optimised with respect to the sugar composition of the fusion medium, duration of hypotonic treatment, frequency range for stable cell alignment, and field strengths of breakdown pulses triggering membrane fusion. The hypotonic electrofusion consistently gave a tumour-DC hybrid rate of up to 19%, as determined by counting dually labelled fluorescent hybrids in a microscope. This fusion rate is nearly twice as high as that usually reported in the literature for isotonic media. The experimental findings and biophysical approach presented here are generally useful for the development of efficient electrofusion protocols, especially for rare and valuable human cells.