Nuclear double-fluorescent reporter for in vivo and ex vivo analyses of biological transitions in mouse nuclei

Cre-responsive dual-fluorescent alleles allow in situ marking of cell lineages or genetically modified cells. Here we report a dual-fluorescent allele, ROSA ^nT-nG , which directs nuclear accumulation of tdTomato in Cre-naïve lineages. Cre converts the allele to ROSA ^nG , which drives nuclear EGFP accumulation. Conditions were established for analyzing marked nuclei by flow cytometry on the basis of red–green fluorescence and ploidy, with a particular focus on liver nuclei. Hydrodynamic delivery of a Cre-expression plasmid was used to time-stamp arbitrary hepatocytes for lineage tracing. The distinct green fluorescence of nuclei from Cre-exposed lineages facilitated analyses of ploidy transitions within clones. To assess developmental transitions in liver nuclei, ROSA ^nT-nG was combined with the hepatocyte-specific AlbCre transgene, facilitating discrimination between hepatocyte and nonhepatocyte nuclei. Nuclei extracted from postnatal day 2 (P2) livers were 41 % green and 59 % red and reached a stable level of 84 % green by P22. Until P20, green nuclei were >98 % diploid (2N); at P40 they were ~56 % 2N, 43 % 4N, and <1 % 8N; and by P70 they reached a stable distribution of ~46 % 2N, 45 % 4N, and 9 % 8N. In conclusion, ROSA ^nT-nG will facilitate in vivo and ex vivo studies on liver and will likely be valuable for studies on tissues like muscle, kidney, or brain in which cells are refractory to whole-cell flow cytometry, or like trophectoderm derivatives or cancers in which cells undergo ploidy transitions.     

The aluminium content of breast tissue taken from women with breast cancer

The aetiology of breast cancer is multifactorial. While there are known genetic predispositions to the disease it is probable that environmental factors are also involved. Recent research has demonstrated a regionally specific distribution of aluminium in breast tissue mastectomies while other work has suggested mechanisms whereby breast tissue aluminium might contribute towards the aetiology of breast cancer. We have looked to develop microwave digestion combined with a new form of graphite furnace atomic absorption spectrometry as a precise, accurate and reproducible method for the measurement of aluminium in breast tissue biopsies. We have used this method to test the thesis that there is a regional distribution of aluminium across the breast in women with breast cancer. Microwave digestion of whole breast tissue samples resulted in clear homogenous digests perfectly suitable for the determination of aluminium by graphite furnace atomic absorption spectrometry. The instrument detection limit for the method was 0.48 μg/L. Method blanks were used to estimate background levels of contamination of 14.80 μg/L. The mean concentration of aluminium across all tissues was 0.39 μg Al/g tissue dry wt. There were no statistically significant regionally specific differences in the content of aluminium. We have developed a robust method for the precise and accurate measurement of aluminium in human breast tissue. There are very few such data currently available in the scientific literature and they will add substantially to our understanding of any putative role of aluminium in breast cancer. While we did not observe any statistically significant differences in aluminium content across the breast it has to be emphasised that herein we measured whole breast tissue and not defatted tissue where such a distribution was previously noted. We are very confident that the method developed herein could now be used to provide accurate and reproducible data on the aluminium content in defatted tissue and oil from such tissues and thereby contribute towards our knowledge on aluminium and any role in breast cancer.     

Examining post‐translational modification‐mediated protein–protein interactions using a chemical proteomics approach

Post‐translational modifications (PTM) of proteins can control complex and dynamic cellular processes via regulating interactions between key proteins. To understand these regulatory mechanisms, it is critical that we can profile the PTM‐dependent protein–protein interactions. However, identifying these interactions can be very difficult using available approaches, as PTMs can be dynamic and often mediate relatively weak protein–protein interactions. We have recently developed CLASPI (cross‐linking‐assisted and stable isotope labeling in cell culture‐based protein identification), a chemical proteomics approach to examine protein–protein interactions mediated by methylation in human cell lysates. Here, we report three extensions of the CLASPI approach. First, we show that CLASPI can be used to analyze methylation‐dependent protein–protein interactions in lysates of fission yeast, a genetically tractable model organism. For these studies, we examined trimethylated histone H3 lysine‐9 (H3K9Me₃)‐dependent protein–protein interactions. Second, we demonstrate that CLASPI can be used to examine phosphorylation‐dependent protein–protein interactions. In particular, we profile proteins recognizing phosphorylated histone H3 threonine‐3 (H3T3‐Phos), a mitotic histone “mark” appearing exclusively during cell division. Our approach identified survivin, the only known H3T3‐Phos‐binding protein, as well as other proteins, such as MCAK and KIF2A, that are likely to be involved in weak but selective interactions with this histone phosphorylation “mark”. Finally, we demonstrate that the CLASPI approach can be used to study the interplay between histone H3T3‐Phos and trimethylation on the adjacent residue lysine 4 (H3K4Me₃). Together, our findings indicate the CLASPI approach can be broadly applied to profile protein–protein interactions mediated by PTMs.     

Is Rapoport's rule a recent phenomenon? A deep time perspective on potential causal mechanisms

Macroecology strives to identify ecological patterns on broad spatial and temporal scales. One such pattern, Rapoport''s rule, describes the tendency of species'' latitudinal ranges to increase with increasing latitude. Several mechanisms have been proposed to explain this rule. Some invoke climate, either through glaciation driving differential extinction of northern species or through increased seasonal variability at higher latitudes causing higher thermal tolerances and subsequently larger ranges. Alternatively, continental tapering or higher interspecific competition at lower latitudes may be responsible. Assessing the incidence of Rapoport''s rule through deep time can help to distinguish between competing explanations. Using fossil occurrence data from the Palaeobiology Database, we test these hypotheses by evaluating mammalian compliance with the rule throughout the Caenozoic of North America. Adherence to Rapoport''s rule primarily coincides with periods of intense cooling and increased seasonality, suggesting that extinctions caused by changing climate may have played an important role in erecting the latitudinal gradients in range sizes seen today.     

A decade of seasonal dynamics and co-occurrences within freshwater bacterioplankton communities from eutrophic Lake Mendota,WI, USA

With an unprecedented decade-long time series from a temperate eutrophic lake, we analyzed bacterial and environmental co-occurrence networks to gain insight into seasonal dynamics at the community level. We found that (1) bacterial co-occurrence networks were non-random, (2) season explained the network complexity and (3) co-occurrence network complexity was negatively correlated with the underlying community diversity across different seasons. Network complexity was not related to the variance of associated environmental factors. Temperature and productivity may drive changes in diversity across seasons in temperate aquatic systems, much as they control diversity across latitude. While the implications of bacterioplankton network structure on ecosystem function are still largely unknown, network analysis, in conjunction with traditional multivariate techniques, continues to increase our understanding of bacterioplankton temporal dynamics.     

Reduction of product-related species during the fermentation and purification of a recombinant IL-1 receptor antagonist at the laboratory and pilot scale

Through a parallel approach of tracking product quality through fermentation and purification development, a robust process was designed to reduce the levels of product-related species. Three biochemically similar product-related species were identified as byproducts of host-cell enzymatic activity. To modulate intracellular proteolytic activity, key fermentation parameters (temperature, pH, trace metals, EDTA levels, and carbon source) were evaluated through bioreactor optimization, while balancing negative effects on growth, productivity, and oxygen demand. The purification process was based on three non-affinity steps and resolved product-related species by exploiting small charge differences. Using statistical design of experiments for elution conditions, a high-resolution cation exchange capture column was optimized for resolution and recovery. Further reduction of product-related species was achieved by evaluating a matrix of conditions for a ceramic hydroxyapatite column. The optimized fermentation process was transferred from the 2-L laboratory scale to the 100-L pilot scale and the purification process was scaled accordingly to process the fermentation harvest. The laboratory- and pilot-scale processes resulted in similar process recoveries of 60 and 65%, respectively, and in a product that was of equal quality and purity to that of small-scale development preparations. The parallel approach for up- and downstream development was paramount in achieving a robust and scalable clinical process.     

Taxonomic Classification of Bacterial 16S rRNA Genes Using Short Sequencing Reads: Evaluation of Effective Study Designs

Massively parallel high throughput sequencing technologies allow us to interrogate the microbial composition of biological samples at unprecedented resolution. The typical approach is to perform high-throughout sequencing of 16S rRNA genes, which are then taxonomically classified based on similarity to known sequences in existing databases. Current technologies cause a predicament though, because although they enable deep coverage of samples, they are limited in the length of sequence they can produce. As a result, high-throughout studies of microbial communities often do not sequence the entire 16S rRNA gene. The challenge is to obtain reliable representation of bacterial communities through taxonomic classification of short 16S rRNA gene sequences. In this study we explored properties of different study designs and developed specific recommendations for effective use of short-read sequencing technologies for the purpose of interrogating bacterial communities, with a focus on classification using naïve Bayesian classifiers. To assess precision and coverage of each design, we used a collection of ∼8,500 manually curated 16S rRNA gene sequences from cultured bacteria and a set of over one million bacterial 16S rRNA gene sequences retrieved from environmental samples, respectively. We also tested different configurations of taxonomic classification approaches using short read sequencing data, and provide recommendations for optimal choice of the relevant parameters. We conclude that with a judicious selection of the sequenced region and the corresponding choice of a suitable training set for taxonomic classification, it is possible to explore bacterial communities at great depth using current technologies, with only a minimal loss of taxonomic resolution.