Increased frequencies of circulating CXCL10-, CXCL8- and CCL4-producing monocytes and Siglec-3-expressing myeloid dendritic cells in systemic sclerosis patients

Objective

To investigate the ex vivo pro-inflammatory properties of classical and non-classical monocytes as well as myeloid dendritic cells (mDCs) in systemic sclerosis (SSc) patients.

Methods

Spontaneous production of CXCL10, CCL4, CXCL8 and IL-6 was intracellularly evaluated in classical, non-classical monocytes and Siglec-3-expressing mDCs from peripheral blood of SSc patients and healthy controls (HC) through flow cytometry. In addition, production of these cytokines was determined upon toll-like receptor (TLR) 4 plus Interferon-γ (IFN-γ) stimulation.

Results

The frequency of non-classical monocytes spontaneously producing CXCL10 was increased in both limited (lcSSc) and diffuse cutaneous (dcSSC) subsets of SSc patients and CCL4 was augmented in dcSSc patients. The proportion of CCL4-producing mDCs was also elevated in dcSSc patients and the percentage of mDCS producing CXCL10 only in lcSSc patients. Upon stimulation, the frequency of non-classical monocytes expressing CXCL8 was increased in both patient groups and mDCs expressing CXCL8 only in lcSSc. Moreover, these parameters in unsupervised clustering analysis identify a subset of patients which are characterized by lung fibrosis and reduced pulmonary function.

Conclusions

These data point towards a role of activated non-classical monocytes and mDCs producing enhanced levels of proinflammatory cytokines in SSc, potentially contributing to lung fibrosis.

     

Two contemporaneous mitogenomes from terminal Pleistocene burials in eastern Beringia

Pleistocene residential sites with multiple contemporaneous human burials are extremely rare in the Americas. We report mitochondrial genomic variation in the first multiple mitochondrial genomes from a single prehistoric population: two infant burials (USR1 and USR2) from a common interment at the Upward Sun River Site in central Alaska dating to ∼11,500 cal B.P. Using a targeted capture method and next-generation sequencing, we determined that the USR1 infant possessed variants that define mitochondrial lineage C1b, whereas the USR2 genome falls at the root of lineage B2, allowing us to refine younger coalescence age estimates for these two clades. C1b and B2 are rare to absent in modern populations of northern North America. Documentation of these lineages at this location in the Late Pleistocene provides evidence for the extent of mitochondrial diversity in early Beringian populations, which supports the expectations of the Beringian Standstill Model.The colonization of the Western Hemisphere has been of interest to scholars since 1590, when Jose de Acosta postulated a northeast Asian origin of the indigenous populations of the Americas (1). Both the archaeological (2, 3) and genetic (4–10) records consistently indicate a primary entry point from Asia to the Americas via the Bering Land Bridge, sometime during the Late Pleistocene. However, there are unfortunate lacunae in both records. The archaeological record indicates a relatively late (<14–16 kya), rapid colonization event following the Last Glacial Maximum. This temporal scale supports the clear northeastward geographical expansion of late Upper Paleolithic (Diuktai) populations from southern and central Siberia to Beringia after 16 kya (5). However, archaeological evidence is accumulating that shows people had penetrated parts of North and South America before 13,250 cal B.P., the earliest date associated with Clovis, the first widespread cultural tradition in North America (2–5, 11).The genetic record is equally problematic. Continental scale analyses of genetic variation rely heavily on Central and South American population data, as well as data from Arctic populations (6–9, 12, 13). Few data exist for North American populations south of the Arctic. Recent surveys of contemporary genetic variation in the Americas are consistent with a period of population isolation during which the distinctive composition of Native American genomes differentiated from ancestral Asian genomes, followed by a rapid colonization; this scenario has been deemed the “Beringian Standstill Model” (6, 7, 10). How early the Native American gene pool diverged remains uncertain, but estimates of up to 30 kya have been postulated (5, 6, 10, 12, 14, 15). Most geneticists argue for at least a several thousand-year period of isolation and genetic differentiation in Beringia before a southward dispersal, despite the absence of supporting archaeological evidence (2, 4, 5, 10). Recently, Raghavan et al. (15), using genome-wide low-coverage data, suggested the dates of this isolation began no earlier than 23 kya and lasted no longer than 8,000 y (15).Ancient DNA (aDNA) samples from early inhabitants of the Americas would be important for linking the modern genetic and archaeological records (16), but few exist. The Mal’ta child from South Central Siberia indicates an early origin (>24 kya) of some signal of Native American ancestry (9), but although a few Pleistocene-aged remains have been recovered in central North America (below the Laurentide Ice Sheet) or along the Northwest Coast, no similarly aged Beringian human remains have previously been available for genetic comparison. Very few Late Pleistocene (>10,000 cal B.P.) individuals have yielded mitochondrial genetic (mtDNA) data, although we highlight the seven sites with ancient human remains dating to >8,000-y-old that have been characterized for mtDNA lineages: Hoyo Negro, Mexico (17); Anzick, MT (18); Kennewick, WA (19); On-Your-Knees Cave, AK; Wizard’s Beach, NV; Hourglass Cave, CO; and, indirectly through coprolite analysis, Paisley Cave, OR (the last four are reviewed in ref. 20) (Fig. 1).Open in a separate windowFig. 1.Geographic map of reported Native American populations with >40% C1 or B2 haplogroup frequencies, as well as locations of archaeological sites discussed. The locations of the Upward Sun River site, as well as the seven previously reported archaeological sites dated at >8,000 y B.P. with successfully genotyped human mitochondrial DNA lineages, are listed on the map (with reported haplotypes). Reported populations of ≥20 individuals with ≥40% C1 (yellow) or B2 (blue) are shown. Populations and frequencies specific to this figure (referenced by numbers 1–50) are available in the SI Materials and Methods.In 2011 Potter et al. (21) reported on the discovery of a cremated 3-y-old child from a residential feature at Upward Sun River (USR) in eastern Beringia dating to 11,500 cal B.P. Additional excavation at this deeply stratified and well-dated site (22) recently yielded two additional infant burials (Fig. 1) (USR1 and USR2) (23). A series of radiocarbon ages securely date the three individuals between 11,600 and 11,270 cal B.P. (23). Based on dental and osteological aging methods, USR1 represents a late preterm fetus, and USR2 likely died within the first 6 wk of life (23). The proximity of these three burials, their context within the same feature, and radiocarbon analyses presented in Potter et al. (23) strongly suggest that all three burials represent nearly contemporaneous events, and that the three individuals were members of a single population.We attempted to extract and sequence the mitochondrial genomes from these three Late Pleistocene burials. From burnt bone fragments of the cremated infant and well-preserved samples of the petrous portion of the parietal bone, DNA was extracted using a silica-based method and attempts were made to Sanger sequence three overlapping fragments of the mitochondrial hypervariable region 1 (HVR1). From USR1 and USR2, all three HVR1 fragments were successfully amplified, and from the cremated infant only one fragment amplified, albeit inconsistently. DNA samples and applicable blank controls from USR1 and USR2 were converted to Ion Torrent Ion Plus Fragment libraries with laboratory-unique barcodes. We targeted the mitochondrial genomes by hybridization capture (24) and sequenced the libraries on two P1 chips with an Ion Proton System (Life Technologies). This is one of the first examples of the Ion Torrent technology applied to aDNA.     

From the Cover: Parasitism alters three power laws of scaling in a metazoan community: Taylor’s law,density-mass allometry,and variance-mass allometry

How do the lifestyles (free-living unparasitized, free-living parasitized, and parasitic) of animal species affect major ecological power-law relationships? We investigated this question in metazoan communities in lakes of Otago, New Zealand. In 13,752 samples comprising 1,037,058 organisms, we found that species of different lifestyles differed in taxonomic distribution and body mass and were well described by three power laws: a spatial Taylor’s law (the spatial variance in population density was a power-law function of the spatial mean population density); density-mass allometry (the spatial mean population density was a power-law function of mean body mass); and variance-mass allometry (the spatial variance in population density was a power-law function of mean body mass). To our knowledge, this constitutes the first empirical confirmation of variance-mass allometry for any animal community. We found that the parameter values of all three relationships differed for species with different lifestyles in the same communities. Taylor''s law and density-mass allometry accurately predicted the form and parameter values of variance-mass allometry. We conclude that species of different lifestyles in these metazoan communities obeyed the same major ecological power-law relationships but did so with parameters specific to each lifestyle, probably reflecting differences among lifestyles in population dynamics and spatial distribution.Variation in population density has long been a central topic in ecology (e.g., ref. 1). Taylor’s law (TL) (2, 3) is a pattern of variation that has been widely verified for population density in basic and applied ecology and for other quantities in other fields. In its ecological interpretations, TL asserts that, in multiple sets of populations, the sample variance in population density within each set is proportional to a power (usually positive) of the sample mean population density within that set. We specify TL in greater detail below.Morand and Guégan (4) showed that TL described well the variations of abundance per host in 828 populations of parasitic nematodes from 66 terrestrial mammalian species. Morand and Krasnov (5) reviewed examples of TL in parasitology and epidemiology and interpreted the exponent of the TL power law in terms of the aggregation of parasites and epidemiological dynamics. These studies used the number of individual parasites per individual host as the measure of population density. Following a suggestion of Taylor (2), these studies interpreted the exponent of the power-law relationship of variance of population density to mean of population density as an index of parasite aggregation among hosts. A purely random distribution of parasites per host leads to a Poisson distribution, which gives a TL exponent equal to 1 as the mean population density varies. A TL exponent greater than 1 reflects greater heterogeneity in numbers of individuals per host than expected from a purely random distribution. More importantly, the TL exponent may also be used to assess the strength of parasite population regulation via processes such as interspecific competition or vaccination, and may distinguish between epidemic and endemic infections (5–7).Here we ask how three lifestyles (free-living unparasitized, free-living parasitized, and parasitic) of animal species affect major ecological power-law relationships, including TL, using new data on all metazoans from the littoral zone of four lakes in coastal and central Otago, South Island, New Zealand. Unlike previous studies of TL in parasitology, we measured the population density of parasites as the number of individuals per square meter of habitat, not per individual host. Additionally, unlike previous studies, in addition to quantifying the population density of parasitic species (separately for each life stage), we quantified the population density of the free-living parasitized species and of the free-living unparasitized species in the same habitat. Contrasting TL and other power-law relationships among organisms with different lifestyles can reveal differences in the degree to which spatial heterogeneity in their abundance is regulated.Using these data, we tested the validity of TL for metazoans of each lifestyle in the same habitat. Intuitively, it seemed plausible, and we investigated the hypothesis, that the interactions of free-living parasitized species and parasites added variability to the population dynamics of species of both lifestyles compared with free-living unparasitized species. This qualitative argument led us to expect larger values of the exponent of TL for free-living parasitized species and parasites compared with the exponent of TL for free-living unparasitized species.In addition to testing TL and the effects of lifestyle on the parameters of TL, we examined the allometric relationship between mean population density and mean body mass (density-mass allometry, or DMA). Marquet et al. (8) and Cohen et al. (9) independently showed theoretically that TL and DMA combine to predict the form and parameters of an allometric relationship between the variance of population density and mean body mass (variance-mass allometry, or VMA). (The details of these predictions are in SI Appendix.) We tested and verified all three relations empirically for each lifestyle in the same habitat. The parameter values of all three relationships depended on lifestyle.Although DMA has been very widely confirmed for a great variety of organisms (e.g., refs. 10–18), including parasitic nematodes (19) and other parasites (20), VMA has previously been confirmed empirically only for congeneric trees (Quercus spp.) in a temperate forest (9). These new data permitted us to verify the predicted VMA empirically, to our knowledge for the first time for any animals and for the first time for all metazoans in a local community. Empirical confirmation of VMA for all metazoans in a local community makes it possible to use average body mass to predict the variability of population densities of different species, in addition to predicting the mean population density from DMA. This variability bears on risks of extinction, population outbreaks, and epidemics. The ability to predict this variability from a factor as easily measured as average body mass could be valuable for economically important species.