CRISPR interference of nucleotide biosynthesis improves production of a single-domain antibody in Escherichia coli

Growth decoupling can be used to optimize the production of biochemicals and proteins in cell factories. Inhibition of excess biomass formation allows for carbon to be utilized efficiently for product formation instead of growth, resulting in increased product yields and titers. Here, we used CRISPR interference to increase the production of a single-domain antibody (sdAb) by inhibiting growth during production. First, we screened 21 sgRNA targets in the purine and pyrimidine biosynthesis pathways and found that the repression of 11 pathway genes led to the increased green fluorescent protein production and decreased growth. The sgRNA targets pyrF, pyrG, and cmk were selected and further used to improve the production of two versions of an expression-optimized sdAb. Proteomics analysis of the sdAb-producing pyrF, pyrG, and cmk growth decoupling strains showed significantly decreased RpoS levels and an increase of ribosome-associated proteins, indicating that the growth decoupling strains do not enter stationary phase and maintain their capacity for protein synthesis upon growth inhibition. Finally, sdAb production was scaled up to shake-flask fermentation where the product yield was improved 2.6-fold compared to the control strain with no sgRNA target sequence. An sdAb content of 14.6% was reached in the best-performing pyrG growth decoupling strain.     

Leaf-cutting ants as road engineers: the width of trails at branching points in <Emphasis Type="Italic">Atta cephalotes</Emphasis>

We used a simple engineering principle, which suggests that the width of a road needed for a smooth traffic flow is proportional to the peak traffic volume (“engineering hypothesis”), to analyze the adaptive significance of trail width at branching points in the leaf-cutting ant Atta cephalotes. Since the flow of outgoing ants splits at trail bifurcations and merges when ants return to the nest through the same paths, the sum of branch widths should equal the width of the trail section upstream of the bifurcation. We measured the width of branches and their preceding trail section and also performed field measurements and manipulations to analyze ant flow, number of collisions, and ant speed in different trail sectors. Contrary to the prediction of the “engineering hypothesis”, the sum of branch widths was larger than the width of the trail immediately before the bifurcation. Our data contradict the “trail addition hypothesis” and support the “border effect hypothesis” to explain this pattern. First, the width of the widest branch was smaller than the width of the trail upstream of the bifurcation, an unexpected result if one branch is merely the continuation of the basal trail. Second, ants collided with obstacles more often in the margin than in the central portion of the trail, relocated ants from central to margin trail sectors reduced their speed, and ant flow was higher in the central sections of the trail. Since the delaying effect of trail margins increases as the trail width decreases, ants may build branches wider than expected to reduce the border effect. The delaying effect of trail margins should be included in the analysis of costs and benefits to fully understand the adaptive value of the design of ant trail networks.     

Future vulnerability mapping based on response to extreme climate events: Dieback thresholds in an endemic California oak

Aim

This study presents a bioclimate modelling approach, using responses to extreme climate events, rather than historical distributional associations, to project future species vulnerability and refugia. We aim to illustrate the compounding effects of groundwater loss and climate on species vulnerability.

Location

California, USA.

Methods

As a case study, we used the 2012–2015 California drought and resulting extensive dieback of blue oak (Quercus douglasii). We used aerial dieback surveys, downscaled climate data and subsurface water change data to develop boosted regression tree models identifying key thresholds associated with dieback throughout the blue oak distribution. We (1) combined observed dieback–climatic threshold relationships with climate futures to anticipate future areas of vulnerability and (2) used satellite‐derived measurements of subsurface water loss in drought/dieback modelling to capture the mediating effect of groundwater on species response to climatic drought.

Results

A model including climate, climate anomalies and subsurface water change explained 46% of the variability in dieback. Precipitation in 2015 and subsurface water change accounted for 62.6% of the modelled probability of dieback. We found an interaction between precipitation and subsurface water in which dieback probability increased with low precipitation and subsurface water loss. The relationship between precipitation and dieback was nonlinear, with 99% of dieback occurring in areas that received <363 mm precipitation. Based on a MIROC_rcp85 future climate scenario, relative to historical conditions, 13% of the blue oak distribution is predicted to experience more frequent years below this precipitation threshold by mid‐century and 81% by end of century.

Main conclusions

As ongoing climate change and extreme events impact ecological processes, the identification of thresholds associated with observed dieback may be combined with climate futures to help identify vulnerable populations and refugia and prioritize climate change‐related conservation efforts.     

Megafauna extinction,tree species range reduction,and carbon storage in Amazonian forests

During the Late Pleistocene and early Holocene 59 species of South American megafauna went extinct. Their extinction potentially triggered population declines of large‐seeded tree species dispersed by the large‐bodied frugivores with which they co‐evolved, a theory first proposed by Janzen and Martin (1982). We tested this hypothesis using species range maps for 257 South American tree species, comparing 63 species thought to be primarily distributed by megafauna with 194 distributed by other animals. We found a highly significant (p < 0.001) decreased mean range size of 26% for the megafauna dispersed fruit (n = 63 species) versus fruit dispersed by other animals (n = 194), results which support the hypothesis. We then developed a mathematical model of seed dispersal to estimate the theoretical impact of megafauna extinction on tree species range and found the estimated dispersal capacity (Φ_seed) of a 2 g seed decreases by > 95% following disperser extinction. A numerical gap dynamic simulations suggests that over a 10 000 yr period following the disperser extinctions, the average convex hull range size of large‐seeded tree species decreased by ～ 31%, while the estimated decrease in population size was ～ 54%, indicating a likely greater decrease in species population size than indicated by the empirical range patterns. Finally, we found a positive correlation between seed size and wood density of animal‐dispersed tree species implying that the Late Pleistocene and early Holocene megafaunal extinctions reduced carbon content in the Amazon by ～ 1.5 ± 0.7%. In conclusion, we 1) provide some empirical evidence that megafauna distributed fruit species have a smaller mean range size than wind, water or other animal‐dispersed species, 2) demonstrate mathematically that such range reductions are expected from megafauna extinctions ca 12 000 yr ago, and 3) illustrate that these extinctions may have reduced the Amazon's carbon storage capacity.     

A network approach for inferring species associations from co‐occurrence data

Positive and negative associations between species are a key outcome of community assembly from regional species pools. These associations are difficult to detect and can be caused by a range of processes such as species interactions, local environmental constraints and dispersal. We integrate new ideas around species distribution modeling, covariance matrix estimation, and network analysis to provide an approach to inferring non‐random species associations from local‐ and regional‐scale occurrence data. Specifically, we provide a novel framework for identifying species associations that overcomes three challenges: 1) correcting for indirect effects from other species, 2) avoiding spurious associations driven by regional‐scale distributions, and 3) describing these associations in a multi‐species context. We highlight a range of research questions and analyses that this framework is able to address. We show that the approach is statistically robust using simulated data. In addition, we present an empirical analysis of > 1000 North American tree communities that gives evidence for weak positive associations among small groups of species. Finally, we discuss several possible extensions for identifying drivers of associations, predicting community assembly, and better linking biogeography and community ecology.     

30% land conservation and climate action reduces tropical extinction risk by more than 50%

Limiting climate change to less than 2°C is the focus of international policy under the climate convention (UNFCCC), and is essential to preventing extinctions, a focus of the Convention on Biological Diversity (CBD). The post-2020 biodiversity framework drafted by the CBD proposes conserving 30% of both land and oceans by 2030. However, the combined impact on extinction risk of species from limiting climate change and increasing the extent of protected and conserved areas has not been assessed. Here we create conservation spatial plans to minimize extinction risk in the tropics using data on 289 219 species and modeling two future greenhouse gas concentration pathways (RCP2.6 and 8.5) while varying the extent of terrestrial protected land and conserved areas from <17% to 50%. We find that limiting climate change to 2°C and conserving 30% of terrestrial area could more than halve aggregate extinction risk compared with uncontrolled climate change and no increase in conserved area.     

Habitat area and climate stability determine geographical variation in plant species range sizes

Despite being a fundamental aspect of biodiversity, little is known about what controls species range sizes. This is especially the case for hyperdiverse organisms such as plants. We use the largest botanical data set assembled to date to quantify geographical variation in range size for ~ 85 000 plant species across the New World. We assess prominent hypothesised range‐size controls, finding that plant range sizes are codetermined by habitat area and long‐ and short‐term climate stability. Strong short‐ and long‐term climate instability in large parts of North America, including past glaciations, are associated with broad‐ranged species. In contrast, small habitat areas and a stable climate characterise areas with high concentrations of small‐ranged species in the Andes, Central America and the Brazilian Atlantic Rainforest region. The joint roles of area and climate stability strengthen concerns over the potential effects of future climate change and habitat loss on biodiversity.     

Patterns and drivers of plant functional group dominance across the Western Hemisphere: a macroecological re‐assessment based on a massive botanical dataset

Plant functional group dominance has been linked to climate, topography and anthropogenic factors. Here, we assess existing theory linking functional group dominance patterns to their drivers by quantifying the spatial distribution of plant functional groups at a 100‐km grid scale. We use a standardized plant species occurrence dataset of unprecedented size covering the entire New World. Functional group distributions were estimated from 3 648 533 standardized occurrence records for a total of 83 854 vascular plant species, extracted from the Botanical Information and Ecology Network (BIEN) database. Seven plant functional groups were considered, describing major differences in structure and function: epiphytes; climbers; ferns; herbs; shrubs; coniferous trees; and angiosperm trees. Two measures of dominance (relative number of occurrences and relative species richness) were analysed against a range of hypothesized predictors. The functional groups showed distinct geographical patterns of dominance across the New World. Temperature seasonality and annual precipitation were most frequently selected, supporting existing hypotheses for the geographical dominance of each functional group. Human influence and topography were secondarily important. Our results support the prediction that future climate change and anthropogenic pressures could shift geographical patterns in dominance of plant functional groups, with probable consequences for ecosystem functioning. © 2015 The Linnean Society of London, Botanical Journal of the Linnean Society, 2016, 180 , 141–160.     

Fluctuations in glucose availability prevent global proteome changes and physiological transition during prolonged chemostat cultivations of Saccharomyces cerevisiae

Chemostat cultivation mode imposes selective pressure on the cells, which may result in slow adaptation in the physiological state over time. We applied a two-compartment scale-down chemostat system imposing feast–famine conditions to characterize the long-term (100 s of hours) response of Saccharomyces cerevisiae to fluctuating glucose availability. A wild-type strain and a recombinant strain, expressing an insulin precursor, were cultured in the scale-down system, and analyzed at the physiological and proteomic level. Phenotypes of both strains were compared with those observed in a well-mixed chemostat. Our results show that S. cerevisiae subjected to long-term chemostat conditions undergoes a global reproducible shift in its cellular state and that this transition occurs faster and is larger in magnitude for the recombinant strain including a significant decrease in the expression of the insulin product. We find that the transition can be completely avoided in the presence of fluctuations in glucose availability as the strains subjected to feast–famine conditions under otherwise constant culture conditions exhibited constant levels of the measured proteome for over 250 hr. We hypothesize possible mechanisms responsible for the observed phenotypes and suggest experiments that could be used to test these mechanisms.