Direct Gene Transfer for the Understanding and Treatment of Human Disease

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/75762/1/j.1749-6632.1994.tb21709.x.pd

Simulating growth-based harvest adaptive to future climate change

Forests are the main source of biomass production from solar energy and take up around 2.4±0.4&thinsp;PgC per year globally. Future changes in climate may affect forest growth and productivity. Currently, state-of-the-art Earth system models use prescribed wood harvest rates in future climate projections. These rates are defined by integrated assessment models (IAMs), only accounting for regional wood demand and largely ignoring the supply side from forests. Therefore, we assess how global growth and harvest potentials of forests change when they are allowed to respond to changes in environmental conditions. For this, we simulate wood harvest rates oriented towards the actual rate of forest growth. Applying this growth-based harvest rule (GB) in JSBACH, the land component of the Max Planck Institute's Earth system model, forced by several future climate scenarios, we realized a growth potential 2 to 4 times (3–9&thinsp;PgC&thinsp;yr−1) the harvest rates prescribed by IAMs (1–3&thinsp;PgC&thinsp;yr−1). Limiting GB to managed forest areas (MF), we simulated a harvest potential of 3–7&thinsp;PgC&thinsp;yr−1, 2 to 3 times higher than IAMs. This highlights the need to account for the dependence of forest growth on climate. To account for the long-term effects of wood harvest as integrated in IAMs, we added a life cycle analysis, showing that the higher supply with MF as an adaptive forest harvesting rule may improve the net mitigation effects of forest harvest during the 21st century by sequestering carbon in anthropogenic wood products.</p

The gene product Murr1 restricts HIV-1 replication in resting CD4(+) lymphocytes

Although human immunodeficiency virus-1 (HIV-1) infects quiescent and proliferating CD4(+) lymphocytes, the virus replicates poorly in resting T cells(1-6). Factors that block viral replication in these cells might help to prolong the asymptomatic phase of HIV infection(7); however, the molecular mechanisms that control this process are not fully understood. Here we show that Murr1, a gene product known previously for its involvement in copper regulation(8,9), inhibits HIV-1 growth in unstimulated CD4(+) T cells. This inhibition was mediated in part through its ability to inhibit basal and cytokine-stimulated nuclear factor (NF)-kappaB activity. Knockdown of Murr1 increased NF-kappaB activity and decreased IkappaB-alpha concentrations by facilitating phospho-IkappaB-alpha degradation by the proteasome. Murr1 was detected in CD4(+) T cells, and RNA-mediated interference of Murr1 in primary resting CD4(+) lymphocytes increased HIV-1 replication. Through its effects on the proteasome, Murr1 acts as a genetic restriction factor that inhibits HIV-1 replication in lymphocytes, which could contribute to the regulation of asymptomatic HIV infection and the progression of AIDS.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/62709/1/nature02171.pd

Slowdown of the greening trend in natural vegetation with further rise in atmospheric CO2_{2}

Satellite data reveal widespread changes in Earth\u27s vegetation cover. Regions intensively attended to by humans are mostly greening due to land management. Natural vegetation, on the other hand, is exhibiting patterns of both greening and browning in all continents. Factors linked to anthropogenic carbon emissions, such as CO$_{2}$ fertilization, climate change, and consequent disturbances such as fires and droughts, are hypothesized to be key drivers of changes in natural vegetation. A rigorous regional attribution at the biome level that can be scaled to a global picture of what is behind the observed changes is currently lacking. Here we analyze different datasets of decades-long satellite observations of global leaf area index (LAI, 1981–2017) as well as other proxies for vegetation changes and identify several clusters of significant long-term changes. Using process-based model simulations (Earth system and land surface models), we disentangle the effects of anthropogenic carbon emissions on LAI in a probabilistic setting applying causal counterfactual theory. The analysis prominently indicates the effects of climate change on many biomes – warming in northern ecosystems (greening) and rainfall anomalies in tropical biomes (browning). The probabilistic attribution method clearly identifies the CO$_{2}$ fertilization effect as the dominant driver in only two biomes, the temperate forests and cool grasslands, challenging the view of a dominant global-scale effect. Altogether, our analysis reveals a slowing down of greening and strengthening of browning trends, particularly in the last 2 decades. Most models substantially underestimate the emerging vegetation browning, especially in the tropical rainforests. Leaf area loss in these productive ecosystems could be an early indicator of a slowdown in the terrestrial carbon sink. Models need to account for this effect to realize plausible climate projections of the 21st century

Climate-Driven Variability and Trends in Plant Productivity Over Recent Decades Based on Three Global Products

Variability in climate exerts a strong influence on vegetation productivity (gross primary productivity; GPP), and therefore has a large impact on the land carbon sink. However, no direct observations of global GPP exist, and estimates rely on models that are constrained by observations at various spatial and temporal scales. Here, we assess the consistency in GPP from global products which extend for more than three decades; two observation‐based approaches, the upscaling of FLUXNET site observations (FLUXCOM) and a remote sensing derived light use efficiency model (RS‐LUE), and from a suite of terrestrial biosphere models (TRENDYv6). At local scales, we find high correlations in annual GPP among the products, with exceptions in tropical and high northern latitudes. On longer time scales, the products agree on the direction of trends over 58% of the land, with large increases across northern latitudes driven by warming trends. Further, tropical regions exhibit the largest interannual variability in GPP, with both rainforests and savannas contributing substantially. Variability in savanna GPP is likely predominantly driven by water availability, although temperature could play a role via soil moisture‐atmosphere feedbacks. There is, however, no consensus on the magnitude and driver of variability of tropical forests, which suggest uncertainties in process representations and underlying observations remain. These results emphasize the need for more direct long‐term observations of GPP along with an extension of in situ networks in underrepresented regions (e.g., tropical forests). Such capabilities would support efforts to better validate relevant processes in models, to more accurately estimate GPP

Dimerization of NF-KB2 with RelA(p65) regulates DNA binding, transcriptional activation, and inhibition by an I kappa B-alpha (MAD-3).

Inducible expression of human immunodeficiency virus (HIV) is regulated by a cellular transcription factor, nuclear factor kappa B (NF-kappa B). NF-kappa B is composed of distinct subunits; five independent genes, NFKB1(p105), NFKB2(p100), RelA(p65), c-rel and relB, that encode related proteins that bind to kappa B DNA elements have been isolated. We have previously found that NFKB2(p49/p52) acts in concert with RelA(p65) to stimulate the HIV enhancer in Jurkat T-leukemia cells. Here we examine the biochemical basis for the transcriptional regulation of HIV by NFKB2. Using Scatchard analysis, we have determined the dissociation constants of homodimeric p49 and heterodimeric p49/p65 for binding to the HIV kappa B site. p49 has a approximately 18-fold-lower affinity for the HIV kappa B site (KD = 69.1 pM) than does the approximately 50-kDa protein NFKB1(p50) derived from p105 (KD = 3.9 pM). In contrast, the affinity of heterodimeric NFKB2(p49)/RelA(p65) for this site is approximately 6-fold higher (KD = 11.8 pM) than that of p49 alone. Consistent with these findings, in vitro transcription was stimulated 18-fold by the addition of preformed, heterodimeric NFKB2(p49)/RelA(p65) protein. Transcriptional activation of the HIV enhancer was also subject to regulation by recently cloned I kappa B-alpha(MAD-3). Recombinant I kappa B-alpha(MAD-3) inhibited the DNA binding activity of p65, p49/p65, and p50/p65 but stimulated the binding of NFKB2(p49) or NFKB1(p50). Functional activation of an HIV reporter plasmid by p49/p65 in transiently transfected Jurkat T-leukemia cells was also inhibited by coexpression of MAD-3. These data suggest that binding of the NFKB2 subunit to the HIV enhancer is facilitated by RelA(p65) and that this NFKB2(p49)/p65 heterodimeric complex mediates transcriptional activation which is subject to regulation by MAD-3

Sources of Uncertainty in Regional and Global Terrestrial CO2 Exchange Estimates

The Global Carbon Budget 2018 (GCB2018) estimated by the atmospheric CO2 growth rate, fossil fuel emissions, and modeled (bottom-up) land and ocean fluxes cannot be fully closed, leading to a “budget imbalance,” highlighting uncertainties in GCB components. However, no systematic analysis has been performed on which regions or processes contribute to this term. To obtain deeper insight on the sources of uncertainty in global and regional carbon budgets, we analyzed differences in Net Biome Productivity (NBP) for all possible combinations of bottom-up and top-down data sets in GCB2018: (i) 16 dynamic global vegetation models (DGVMs), and (ii) 5 atmospheric inversions that match the atmospheric CO2 growth rate. We find that the global mismatch between the two ensembles matches well the GCB2018 budget imbalance, with Brazil, Southeast Asia, and Oceania as the largest contributors. Differences between DGVMs dominate global mismatches, while at regional scale differences between inversions contribute the most to uncertainty. At both global and regional scales, disagreement on NBP interannual variability between the two approaches explains a large fraction of differences. We attribute this mismatch to distinct responses to El Niño–Southern Oscillation variability between DGVMs and inversions and to uncertainties in land use change emissions, especially in South America and Southeast Asia. We identify key needs to reduce uncertainty in carbon budgets: reducing uncertainty in atmospheric inversions (e.g., through more observations in the tropics) and in land use change fluxes, including more land use processes and evaluating land use transitions (e.g., using high-resolution remote-sensing), and, finally, improving tropical hydroecological processes and fire representation within DGVMs.</p