Regulation of albumin gene expression in a series of rat hepatocyte cell lines immortalized by simian virus 40 and maintained in chemically defined medium.

A series of simian virus 40 (SV40)-immortalized hepatocyte cell lines were characterized for albumin production, the regulation of albumin production, and the expression of other liver-specific genes. This series of cell lines is particularly useful for studying the regulation of hepatocyte gene expression because the cell lines express liverlike levels of a number of liver-specific functions and do so while growing in a chemically defined medium. SV40-immortalized hepatocyte cell lines were derived from colonies of albumin-producing epithelial cells that arose after primary hepatocytes maintained in chemically defined medium were transfected with SV40 DNA. Some cell lines secreted albumin at levels equal to or greater than those secreted by freshly plated primary hepatocytes, and all but one line continued to produce albumin for more than 20 passages. The variation in albumin secretion among cell lines reflected differences in the amount of albumin produced per cell and not in the percentage of albumin-producing cells in each line. The characterization of selected cell lines showed that albumin production was regulated by cell density during the growth cycle. Albumin production in most cell lines was also regulated by dexamethasone; however, one cell line continued to produce high levels of albumin when the cells were grown in medium lacking dexamethasone, demonstrating that although glucocorticoid can induce albumin production in some cell lines, it is not required for high levels of albumin production by all cells in culture. Regulation of albumin production measured at the level of protein secretion was paralleled by changes in steady-state levels of a 2.3-kilobase albumin RNA. Albumin-producing SV40-immortalized hepatocytes secreted a variety of other plasma proteins, including transferrin, hemopexin, and the third component of complement. These cells also expressed tyrosine aminotransferase activity that was inducible by dexamethasone. Alpha-fetoprotein production was not detected in any of the cell lines examined.     

Subcellular proteomics for determining iron-limited remodeling of plastids in the model diatom Thalassiosira pseudonana (Bacillariophyta)

Diatoms are important primary producers in the world's oceans, yet their growth is constrained in large regions by low bioavailable iron (Fe). Low-Fe stress-induced limitation of primary production is due to requirements for Fe in components of essential metabolic pathways including photosynthesis and other chloroplast plastid functions. Studies have shown that under low-Fe stress, diatoms alter plastid-specific processes, including components of electron transport. These physiological changes suggest changes of protein content and in protein abundances within the diatom plastid. While in silico predictions provide putative information on plastid-localized proteins, knowledge of diatom plastid proteins remains limited in comparison to well-studied model photosynthetic organisms. To address this, we employed shotgun proteomics to investigate the proteome of subcellular plastid-enriched fractions from Thalassiosira pseudonana to gain a better understanding of how the plastid proteome is remodeled in response to Fe limitation. Using mass spectrometry-based peptide identification and quantification, we analyzed T. pseudonana grown under Fe-replete and -limiting conditions. Through these analyses, we inferred the relative quantities of each protein, revealing that Fe limitation regulates major metabolic pathways in the plastid, including the Calvin cycle. Additionally, we observed changes in the expression of light-harvesting proteins. In silico localization predictions of proteins identified in this plastid-enriched proteome allowed for an in-depth comparison of theoretical versus observed plastid-localization, providing evidence for the potential of additional protein import pathways into the diatom plastid.     

The nucleotide sequence of rabbit liver transferrin cDNA

The cDNA sequence of rabbit liver transferrin has been determined. The largest cDNA was 2279 base pairs (bp) in size and encoded 694 amino acids consisting of a putative 19 amino acid signal peptide and 675 amino acids of plasma transferrin. The deduced amino acid sequence of rabbit liver transferrin shares 78.5% identity with human liver transferrin and 69.1% and 44.8% identity with porcine and Xenopus transferrins, respectively. At the amino acid level, vertebrate transferrins share 26.4% identity and 56.5% similarity. The most conserved regions correspond to the iron ligands and the anion binding region. Optimal alignment of transferrin sequences required the insertion of a number of gaps in the region corresponding to the N-lobe. In addition, the N-lobes of transferrins share less amino acid sequence similarity than the C-lobes.     

Between a rock and a hard place: adaptive sensing and site‐specific dispersal

Environmental variability can lead to dispersal: why stay put if it is better elsewhere? Without clues about local conditions, the optimal strategy is often to disperse a set fraction of offspring. Many habitats contain environmentally differing sub‐habitats. Is it adaptive for individuals to sense in which sub‐habitat they find themselves, using environmental clues, and respond plastically by altering the dispersal rates? This appears to be done by some plants which produce dimorphic seeds with differential dispersal properties in response to ambient temperature. Here we develop a mathematical model to show, that in highly variable environments, not only does sensing promote plasticity of dispersal morph ratio, individuals who can sense their sub‐habitat and respond in this way have an adaptive advantage over those who cannot. With a rise in environmental variability due to climate change, our understanding of how natural populations persist and respond to changes has become crucially important.     

Projected climate impacts to South African maize and wheat production in 2055: a comparison of empirical and mechanistic modeling approaches

Crop model‐specific biases are a key uncertainty affecting our understanding of climate change impacts to agriculture. There is increasing research focus on intermodel variation, but comparisons between mechanistic (MMs) and empirical models (EMs) are rare despite both being used widely in this field. We combined MMs and EMs to project future (2055) changes in the potential distribution (suitability) and productivity of maize and spring wheat in South Africa under 18 downscaled climate scenarios (9 models run under 2 emissions scenarios). EMs projected larger yield losses or smaller gains than MMs. The EMs’ median‐projected maize and wheat yield changes were ?3.6% and 6.2%, respectively, compared to 6.5% and 15.2% for the MM. The EM projected a 10% reduction in the potential maize growing area, where the MM projected a 9% gain. Both models showed increases in the potential spring wheat production region (EM = 48%, MM = 20%), but these results were more equivocal because both models (particularly the EM) substantially overestimated the extent of current suitability. The substantial water‐use efficiency gains simulated by the MMs under elevated CO₂ accounted for much of the EM?MM difference, but EMs may have more accurately represented crop temperature sensitivities. Our results align with earlier studies showing that EMs may show larger climate change losses than MMs. Crop forecasting efforts should expand to include EM?MM comparisons to provide a fuller picture of crop–climate response uncertainties.