Life cycle assessment of forest biomass energy feedstock in the Northeast United States

Life cycle assessment (LCA) was combined with primary data from nine forest harvesting operations in New York, Maine, Massachusetts, and Vermont, from 2013 to 2019 where forest biomass (FB) for bioenergy was one of several products. The objective was to conduct a data‐driven study of greenhouse gas emissions associated with FB feedstock harvesting operations in the Northeast United States. Deterministic and stochastic LCA models were built to simulate the current FB bioenergy feedstock supply chain in the Northeast US with a cradle‐to‐gate scope (forest harvest through roadside loading) and a functional unit of 1.0 Mg of green FB feedstock at a 50% moisture content. Baseline LCA, sensitivity analysis, and uncertainty analyses were conducted for three different FB feedstock types—dirty chips, clean chips, and grindings—enabling an empirically driven investigation of differences between feedstock types, individual harvesting process contributions, and literature comparisons. The baseline LCA average impacts were lower for grindings (4.57 kg CO_2eq/Mg) and dirty chips (7.16 kg CO_2eq/Mg) than for clean chips (23.99 kg CO_2eq/Mg) under economic allocation, but impacts were of similar magnitude under mass allocation, ranging from 24.42 to 27.89 kg CO_2eq/Mg. Uncertainty analysis showed a wider range of probable results under mass allocation compared to economic allocation. Sensitivity analysis revealed the impact of variations in the production masses and total economic values of primary products of forest harvests on the LCA results due to allocation of supply chain emissions. The high variability in fuel use between logging contractors also had a distinct influence on LCA results. The results of this study can aid decision‐makers in energy policy and guide emissions reductions efforts while informing future LCAs that expand the system boundary to regional FB energy pathways, including electricity generation, transportation fuels, pellets for heat, and combined heat and power.     

Postglacial recolonization of North America by spadefoot toads: integrating niche and corridor modeling to study species’ range dynamics over geologic time

Understanding the factors that shape species’ distributions is a key topic in biogeography. As climates change, species can either cope with these changes through evolution, plasticity or by shifting their ranges to track the optimal climatic conditions. Ecological niche modeling (ENM) is a widespread technique in biogeography that estimates the niche of the organism by using occurrences and environmental data to estimate species’ potential distributions. ENMs are often criticized for failing to take species’ dispersal abilities into consideration. Here, we attempt to fill this gap by combining ENMs with dispersal and corridor modeling to study the range dynamics of North American spadefoot toads (Scaphiopodidae) over the Holocene. We first estimated the current and past distributions of spadefoot toads and then estimated their past distributions from the Last Glacial Maximum (LGM) to the present day. Then, we estimated how each taxon recolonized North American by using dispersal and corridor modeling. By combining these two modeling approaches we were able to 1) estimate the LGM refugia used by the North American spadefoot toads, 2) further refine these projections by estimating which of the putative LGM refugia contributed to the recolonization of North America via dispersal, and 3) estimate the relative influence of each LGM refugium to the current species’ distributions. The models were tested using previously published phylogeographic data, revealing a high degree of congruence between our models and the genetic data. These results suggest that combining ENMs and dispersal modeling over time is a promising approach to investigate both historical and future species’ range dynamics.     

Uncovering the evolutionary origin of blue anthocyanins in cereal grains

Functional divergence after gene duplication plays a central role in plant evolution. Among cereals, only Hordeum vulgare (barley), Triticum aestivum (wheat) and Secale cereale (rye) accumulate delphinidin‐derived (blue) anthocyanins in the aleurone layer of grains, whereas Oryza sativa (rice), Zea mays (maize) and Sorghum bicolor (sorghum) do not. The underlying genetic basis for this natural occurrence remains elusive. Here, we mapped the barley Blx1 locus involved in blue aleurone to an approximately 1.13 Mb genetic interval on chromosome 4HL, thus identifying a trigenic cluster named MbHF35 (containing HvMYB4H, HvMYC4H and HvF35H). Sequence and expression data supported the role of these genes in conferring blue‐coloured (blue aleurone) grains. Synteny analyses across monocot species showed that MbHF35 has only evolved within distinct Triticeae lineages, as a result of dispersed gene duplication. Phylogeny analyses revealed a shared evolution pattern for MbHF35 in Triticeae, suggesting that these genes have co‐evolved together. We also identified a Pooideae‐specific flavonoid 3′,5′‐hydroxylase (F3′5′H) lineage, termed here Mo_F35H2, which has a higher amino acid similarity with eudicot F3′5′Hs, demonstrating a scenario of convergent evolution. Indeed, selection tests identified 13 amino acid residues in Mo_F35H2 that underwent positive selection, possibly driven by protein thermostablility selection. Furthermore, through the interrogation of barley germplasm there is evidence that HvMYB4H and HvMYC4H have undergone human selection. Collectively, our study favours blue aleurone as a recently evolved trait resulting from environmental adaptation. Our findings provide an evolutionary explanation for the absence of blue anthocyanins in other cereals and highlight the importance of gene functional divergence for plant diversity and environmental adaptation.     

Interactions among Triatoma sanguisuga blood feeding sources,gut microbiota and Trypanosoma cruzi diversity in southern Louisiana

Integrating how biodiversity and infectious disease dynamics are linked at multiple levels and scales is highly challenging. Chagas disease is a vector‐borne disease, with specificities of the triatomine vectors and Trypanosoma cruzi parasite life histories resulting in a complex multihost and multistrain life cycle. Here, we tested the hypothesis that T. cruzi transmission cycles are shaped by triatomine host communities and gut microbiota composition by comparing the integrated interactions of Triatoma sanguisuga in southern Louisiana with feeding hosts, T. cruzi parasite and bacterial microbiota in two habitats. Bugs were collected from resident's houses and animal shelters and analysed for genetic structure, blood feeding sources, T. cruzi parasites, and bacterial diversity by PCR amplification of specific DNA markers followed by next‐generation sequencing, in an integrative metabarcoding approach. T. sanguisuga feeding host communities appeared opportunistic and defined by host abundance in each habitat, yielding distinct parasite transmission networks among hosts. The circulation of a large diversity of T. cruzi DTUs was also detected, with TcII and TcV detected for the first time in triatomines in the US. The bacterial microbiota was highly diverse and varied significantly according to the DTU infecting the bugs, indicating specific interactions among them in the gut. Expanding such studies to multiple habitats and additional triatomine species would be key to further refine our understanding of the complex life cycles of multihost, multistrain parasites such as T. cruzi, and may lead to improved disease control strategies.     

Integration of high-throughput analytics and cell imaging enables direct early productivity and product quality assessment during Chinese Hamster ovary cell line development for a complex multi-subunit vaccine antigen

Mammalian cell line generation typically includes stable pool generation, single cell cloning and several rounds of clone selection based on cell growth, productivity and product quality criteria. Individual clone expansion and phenotype-based ranking is performed initially for hundreds or thousands of mini-scale cultures, representing the major operational challenge during cell line development. Automated cell culture and analytics systems have been developed to enable high complexity clone selection workflows; while ensuring traceability, safety, and quality of cell lines intended for biopharmaceutical applications. Here we show that comprehensive and quantitative assessment of cell growth, productivity, and product quality attributes are feasible at the 200–1,200 cell colony stage, within 14 days of the single cell cloning in static 96-well plate culture. The early cell line characterization performed prior to the clone expansion in suspension culture can be used for a single-step, direct selection of high quality clones. Such clones were comparable, both in terms of productivity and critical quality attributes (CQAs), to the top-ranked clones identified using an established iterative clone screening approach. Using a complex, multi-subunit antigen as a model protein, we observed stable CQA profiles independently of the cell culture format during the clonal expansion as well as in the batch and fed-batch processes. In conclusion, we propose an accelerated clone selection approach that can be readily incorporated into various cell line development workstreams, leading to significant reduction of the project timelines and resource requirements.