Impacts of metal stress on extracellular microbial products, and potential for selective metal recovery.

Harnessing microbial capabilities for metal recovery from secondary waste sources is an eco-friendly and sustainable approach for the management of metal-containing wastes. Soluble microbial products (SMP) and extracellular polymeric substances (EPS) are the two main groups of extracellular compounds produced by microorganisms in response to metal stress that are of great importance for remediation and recovery of metals. These include various high-, and low, molecular weight components, which serve various functional and structural roles. These compounds often contain functional groups with metal binding potential that can attenuate metal stress by sequestering metal ions, making them less bioavailable. Microorganisms can regulate the content and composition of EPS and SMP in response to metal stress in order to increase the compounds specificity and capacity for metal binding. Thus, EPS and SMP represent ideal candidates for developing technologies for selective metal recovery from complex wastes. To discover highly metal-sorptive compounds with specific metal binding affinity for metal recovery applications, it is necessary to investigate the metal binding affinity of these compounds, especially under metal stressed conditions. In this review we critically reviewed microbial EPS and SMP production as a response to metal stress with a particular emphasis on the metal binding properties of these compounds and their role in altering metal bioavailability. Furthermore, for the first time, we compiled the available data on potential application of these compounds for selective metal recovery from waste streams.

Interrelating EPS, soluble microbial products and metal solubility in a methanogenic consortium stressed by nickel and cobalt.

The relationships between extracellular polymeric substances (EPS), soluble microbial product production, metal solubility, and methanogenic activity were investigated. The individual, and joint, toxic effects of nickel and cobalt on methanogenic consortia fed with glucose as model substrate were studied using biomethane potential assays. Cobalt was found to be less toxic to methanogens than nickel at each concentration tested, and the combined effects of Ni and Co on methane production in the bimetal experiment was higher than the sum of the effects of each metal alone. The protein content of EPS, and extracellular soluble protein fractions, decreased with increasing concentrations of total metals. Meanwhile, no significant change in response to metal stress was apparent for carbohydrate content of EPS or extracellular soluble carbohydrate. Decreasing protein content of EPS was accompanied by reduced methanogenic activity and an increase in the soluble metal fraction. The strong associations observed between these variables could be due to the critical role of EPS in protecting microbial cells against nickel and cobalt stress, possibly by capturing metal cations through their functional groups, thus reducing metal availability to the microbial cells in the methanogenic consortia underpinning the anaerobic digestion process.

Methanogenic granule growth and development is a continual process characterized by distinct morphological features.

Up-flow anaerobic bioreactors are widely applied for high-rate digestion of industrial wastewaters and rely on formation, and retention, of methanogenic granules, comprising of dense, fast-settling, microbial aggregates (approx. 0.5-4.0 mm in diameter). Granule formation (granulation) mechanisms have been reasonably well hypothesized and documented. However, this study used laboratory-scale bioreactors, inoculated with size-separated granular sludge to follow new granule formation, maturation, disintegration and re-formation. Temporal size profiles, volatile solids content, settling velocity, and ultrastructure of granules were determined from each of four bioreactors inoculated only with small granules, four with only large granules, and four with a full complement of naturally-size-distributed granules. Constrained granule size profiles shifted toward the natural distribution, which was associated with maximal bioreactor performance. Distinct morphological features characterized different granule sizes and biofilm development stages, including 'young', 'juvenile', 'mature' and 'old'. The findings offer opportunities toward optimizing management of high-rate, anaerobic digesters by shedding light on the rates of granule growth, the role of flocculent sludge in granulation and how shifting size distributions should be considered when setting upflow velocities.

Predicting vertical ground reaction force during running using novel piezoresponsive sensors and accelerometry.

Running is a common exercise with numerous health benefits. Vertical ground reaction force (vGRF) influences running injury risk and running performance. Measurement of vGRF during running is now primarily constrained to a laboratory setting. The purpose of this study was to evaluate a new approach to measuring vGRF during running. This approach can be used outside of the laboratory and involves running shoes instrumented with novel piezoresponsive sensors and a standard accelerometer. Thirty-one individuals ran at three different speeds on a force-instrumented treadmill while wearing the instrumented running shoes. vGRF was predicted using data collected from the instrumented shoes, and predicted vGRF were compared to vGRF measured via the treadmill. Per cent error of the resulting predictions varied depending upon the predicted vGRF characteristic. Per cent error was relatively low for predicted vGRF impulse (2-7%), active peak vGRF (3-7%), and ground contact time (3-6%), but relatively high for predicted vGRF load rates (22-29%). These errors should decrease with future iterations of the instrumented shoes and collection of additional data from a more diverse sample. The novel technology described herein might become a feasible way to collect large amounts of vGRF data outside of the traditional biomechanics laboratory.

Acetotrophic Activity Facilitates Methanogenesis from LCFA at Low Temperatures: Screening from Mesophilic Inocula.

The inoculum source plays a crucial role in the anaerobic treatment of wastewaters. Lipids are present in various wastewaters and have a high methanogenic potential, but their hydrolysis results in the production of long chain fatty acids (LCFAs) that are inhibitory to anaerobic microorganisms. Screening of inoculum for the anaerobic treatment of LCFA-containing wastewaters has been performed at mesophilic and thermophilic conditions. However, an evaluation of inocula for producing methane from LCFA-containing wastewater has not yet been conducted at low temperatures and needs to be undertaken. In this study, three inocula (one granular sludge and two municipal digester sludges) were assessed for methane production from LCFA-containing synthetic dairy wastewater (SDW) at low temperatures (10 and 20°C). A methane yield (based on mL-CH4/g-CODadded) of 86-65% with acetate and 45-20% with SDW was achieved within 10 days using unacclimated granular sludge, whereas the municipal digester sludges produced methane only at 20°C but not at 10°C even after 200 days of incubation. The acetotrophic activity in the inoculum was found to be crucial for methane production from LCFA at low temperatures, highlighting the role of Methanosaeta (acetoclastic archaea) at low temperatures. The presence of bacterial taxa from the family Syntrophaceae (Syntrophus and uncultured taxa) in the inoculum was found to be important for methane production from SDW at 10°C. This study suggests the evaluation of acetotrophic activity and the initial microbial community characteristics by high-throughput amplicon sequencing for selecting the inoculum for producing methane at low temperatures (up to 10°C) from lipid-containing wastewaters.

Elemental sulfur-based autotrophic denitrification and denitritation: microbially catalyzed sulfur hydrolysis and nitrogen conversions.

The hydrolysis of elemental sulfur (S0) coupled to S0-based denitrification and denitritation was investigated in batch bioassays by microbiological and modeling approaches. In the denitrification experiments, the highest obtained NO3--N removal rate was 20.9 mg/l·d. In the experiments with the biomass enriched on NO2-, a NO2--N removal rate of 10.7 mg/l·d was achieved even at a NO2--N concentration as high as 240 mg/l. The Helicobacteraceae family was only observed in the biofilm attached onto the chemically-synthesized S0 particles with a relative abundance up to 37.1%, suggesting it was the hydrolytic biomass capable of S0 solubilization in the novel surface-based model. S0-driven denitrification was modeled as a two-step process in order to explicitly account for the sequential reduction of NO3- to NO2- and then to N2 by denitrifying bacteria.

Biogas-based denitrification in a biotrickling filter: Influence of nitrate concentration and hydrogen sulfide.

The feasibility of NO3- removal by the synergistic action of a prevailing denitrifying anoxic methane oxidising (DAMO), and nitrate-reducing and sulfide-oxidising bacterial (NR-SOB) consortium, using CH4 and H2 S from biogas as electron donors in a biotrickling filter was investigated. The influence of NO3- concentration on N2 O production during this process was also evaluated. The results showed that NO3- was removed at rates up to 2.8 g mreactor-3 h-1 using CH4 as electron donor. N2 O production rates correlated with NO3- concentration in the liquid phase, with a 10-fold increase in N2 O production as NO3- concentration increased from 50 to 200 g m-3 . The use of H2 S as co-electron donor resulted in a 13-fold increase in NO3- removal rates (∼18 gNO3- m-3 h-1 ) and complete denitrification under steady-state conditions, which was supported by higher abundances of narG, nirK, and nosZ denitrifying genes. Although the relative abundance of the DAMO population in the consortium was reduced from 60% to 13% after H2 S addition, CH4 removals were not compromised and H2 S removal efficiencies of 100% were achieved. This study confirmed (i) the feasibility of co-oxidising CH4 and H2 S with denitrification, as well as (ii) the critical need to control NO3- concentration to minimize N2 O production by anoxic denitrifiers. Biotechnol. Bioeng. 2017;114: 665-673. © 2016 Wiley Periodicals, Inc.

Bioaugmentation Mitigates the Impact of Estrogen on Coliform-Grazing Protozoa in Slow Sand Filters.

Exposure to endocrine-disrupting chemicals (EDCs), such as estrogens, is a growing issue for human and animal health as they have been shown to cause reproductive and developmental abnormalities in wildlife and plants and have been linked to male infertility disorders in humans. Intensive farming and weather events, such as storms, flash flooding, and landslides, contribute estrogen to waterways used to supply drinking water. This paper explores the impact of estrogen exposure on the performance of slow sand filters (SSFs) used for water treatment. The feasibility and efficacy of SSF bioaugmentation with estrogen-degrading bacteria was also investigated, to determine whether removal of natural estrogens (estrone, estradiol, and estriol) and overall SSF performance for drinking water treatment could be improved. Strains for SSF augmentation were isolated from full-scale, municipal SSFs so as to optimize survival in the laboratory-scale SSFs used. Concentrations of the natural estrogens, determined by gas chromatography coupled with mass spectrometry (GC-MS), revealed augmented SSFs reduced the overall estrogenic potency of the supplied water by 25% on average and removed significantly more estrone and estradiol than nonaugmented filters. A negative correlation was found between coliform removal and estrogen concentration in nonaugmented filters. This was due to the toxic inhibition of protozoa, indicating that high estrogen concentrations can have functional implications for SSFs (such as impairing coliform removal). Consequently, we suggest that high estrogen concentrations could impact significantly on water quality production and, in particular, on pathogen removal in biological water filters.

Ammonia oxidizing bacteria and archaea in horizontal flow biofilm reactors treating ammonia-contaminated air at 10 °C.

The objective of this study was to demonstrate the feasibility of novel, Horizontal Flow Biofilm Reactor (HFBR) technology for the treatment of ammonia (NH3)-contaminated airstreams. Three laboratory-scale HFBRs were used for remediation of an NH3-containing airstream at 10 °C during a 90-d trial to test the efficacy of low-temperature treatment. Average ammonia removal efficiencies of 99.7 % were achieved at maximum loading rates of 4.8 g NH3 m(3) h(-1). Biological nitrification of ammonia to nitrite (NO2 (-)) and nitrate (NO3 (-)) was mediated by nitrifying bacterial and archaeal biofilm populations. Ammonia-oxidising bacteria (AOB) were significantly more abundant than ammonia-oxidising archaea (AOA) vertically at each of seven sampling zones along the vertical HFBRs. Nitrosomonas and Nitrosospira, were the two most dominant bacterial genera detected in the HFBRs, while an uncultured archaeal clone dominated the AOA community. The bacterial community composition across the three HFBRs was highly conserved, although variations occurred between HFBR zones and were driven by physicochemical variables. The study demonstrates the feasibility of HFBRs for the treatment of ammonia-contaminated airstreams at low temperatures; identifies key nitrifying microorganisms driving the removal process; and provides insights for process optimisation and control. The findings are significant for industrial applications of gas oxidation technology in temperate climates.

Removal of metals and emergent contaminants from liquid digestates in constructed wetlands for agricultural reuse.

Given the increasing pressure on water bodies, it is imperative to explore sustainable methodologies for wastewater treatment and reuse. The simultaneous presence of multiples contaminants in complex wastewater, such as the liquid effluents from biogas plants, can compromise biological treatment effectiveness for reclaiming water. Vertical subsurface flow constructed wetlands were established as low-cost decentralized wastewater treatment technologies to treat the liquid fraction of digestate from municipal organic waste with metals, antibiotics, and antibiotic resistance genes, to allow its reuse in irrigation. Twelve lab-scale planted constructed wetlands were assembled with gravel, light expanded clay aggregate and sand, testing four different treating conditions (liquid digestate spiked with oxytetracycline, sulfadiazine, or ofloxacin, at 100 µg/ L, or without dosing) during 3 months. Physicochemical parameters (pH, chemical oxygen demand (COD), nutrients, metals, and antibiotics), the microbial communities dynamics (through 16S high-throughput sequencing) and antibiotic resistance genes removal (qPCR) were monitored in influents and effluents. Systems removed 85.8%-96.9% of organic matter (as COD), over 98.1% of ammonium and phosphate ions, and 69.3%-99.4% of nitrate and nitrite ions, with no significant differences between the presence or absence of antibiotics. Removal of Fe, Mn, Zn, Cu, Pb and Cr exceeded 82% in all treatment cycles. The treatment also removed oxytetracycline, sulfadiazine and ofloxacin over 99%, and decreased intl1, tetA, tetW, sul1 and qnrS gene copies. Nonetheless, after 3 months of ofloxacin dosing, qnrS gene started being detected. Removal processes relied on high HRT (14 days) and various mechanisms including sorption, biodegradation, and precipitation. Microbial community diversity in liquid digestate changed significantly after treatment in constructed wetlands with a decrease in the initial Firmicutes dominance, but with no clear effect of antibiotics on the microbial community structure. Removals above 85% and 94% were observed for Streptococcus and Clostridium, respectively. Results suggest that vertical subsurface flow constructed wetlands were a suitable technology for treating the liquid digestate to reuse it in irrigation agricultural systems, contributing to the circular bioeconomy concept. However, a more profound understanding of effective wastewater treatment strategies is needed to avoid antibiotic resistance genes dissemination.

Dynamic gill and mucus microbiomes during a gill disease episode in farmed Atlantic salmon.

Amoebic gill disease (AGD) and complex gill disease (CGD) are recurrent gill disorders in Atlantic salmon, resulting in significant aquaculture losses. The role of gill microbiomes in gill disease development is unclear. We undertook a longitudinal study to characterise the gill tissue and gill mucus microbiomes of farmed Atlantic salmon before, and during, a gill disease episode. Using a newly optimised DNA extraction protocol, we sequenced rRNA genes from microbiomes of gill samples taken from 105 individual salmon on a farm, over a summer season. The AGD aetiological agent, Neoparamoeba perurans, was PCR-quantified targeting 18S rRNA genes. Similar analyses were carried out on mucus samples. Mucus scrapings were suitable, non-lethal substitutes for characterisation of the gill prokaryotic community in this study. Gill tissue and gill mucus microbiomes changed during the campaign, correlating with N. perurans concentrations. Time explained 35% of the gill tissue and gill mucus microbiome variance, while N. perurans concentrations explained 5%. Genera including Dyadobacter, Shewanella and Pedobacter were maximally abundant in gill and mucus samples at the timepoint prior to the the detection of gill disorder signs, at T3. Shewanella was significantly more abundant before than during the gill disease episode, and we suggest this genus could be considered in future studies addressing relationships between gill disease and the gill microbiome.

A meta-analysis of acetogenic and methanogenic microbiomes in microbial electrosynthesis.

A meta-analysis approach was used, to study the microbiomes of biofilms and planktonic communities underpinning microbial electrosynthesis (MES) cells. High-throughput DNA sequencing of 16S rRNA gene amplicons has been increasingly applied to understand MES systems. In this meta-analysis of 22 studies, we find that acetogenic and methanogenic MES cells share 80% of a cathodic core microbiome, and that different inoculum pre-treatments strongly affect community composition. Oxygen scavengers were more abundant in planktonic communities, and several key organisms were associated with operating parameters and good cell performance. We suggest Desulfovibrio sp. play a role in initiating early biofilm development and shaping microbial communities by catalysing H2 production, to sustain either Acetobacterium sp. or Methanobacterium sp. Microbial community assembly became more stochastic over time, causing diversification of the biofilm (cathodic) community in acetogenic cells and leading to re-establishment of methanogens, despite inoculum pre-treatments. This suggests that repeated interventions may be required to suppress methanogenesis.

Microbial community assembly and dynamics in Granular, Fixed-Biofilm and planktonic microbiomes valorizing Long-Chain fatty acids at 20 °C.

Distinct microbial assemblages evolve in anaerobic digestion (AD) reactors to drive sequential conversions of organics to methane. The spatio-temporal development of three such assemblages (granules, biofilms, planktonic) derived from the same inoculum was studied in replicated bioreactors treating long-chain fatty acids (LCFA)-rich wastewater at 20 °C at hydraulic retention times (HRTs) of 12-72 h. We found granular, biofilm and planktonic assemblages differentiated by diversity, structure, and assembly mechanisms; demonstrating a spatial compartmentalisation of the microbiomes from the initial community reservoir. Our analysis linked abundant Methanosaeta and Syntrophaceae-affiliated taxa (Syntrophus and uncultured) to their putative, active roles in syntrophic LCFA bioconversion. LCFA loading rates (stearate, palmitate), and HRT, were significant drivers shaping microbial community dynamics and assembly. This study of the archaea and syntrophic bacteria actively valorising LCFAs at short HRTs and 20 °C will help uncover the microbiology underpinning anaerobic bioconversions of fats, oil and grease.

Biofilm carrier type affects biogenic sulfur-driven denitrification performance and microbial community dynamics in moving-bed biofilm reactors.

Autotrophic denitrification with biosulfur (ADBIOS) provides a sustainable technological solution for biological nitrogen removal from wastewater driven by biogenic S0, derived from biogas desulfurization. In this study, the effect of different biofilm carriers (conventional AnoxK™ 1 and Z-200 with a pre-defined maximum biofilm thickness) on ADBIOS performance and microbiomics was investigated in duplicate moving bed-biofilm reactors (MBBRs). The MBBRs were operated parallelly in continuous mode for 309 days, whilst gradually decreasing the hydraulic retention time (HRT) from 72 to 21 h, and biosulfur was either pumped in suspension (days 92-223) or supplied in powder form. Highest nitrate removal rates were approximately 225 (±11) mg/L·d and 180 (±7) mg NO3--N/L·d in the MBBRs operated with K1 and Z-200 carriers, respectively. Despite having the same protected surface area for biofilm development in each MBBR, the biomass attached onto the K1 carrier was 4.8-fold more than that on the Z-200 carrier, with part of the biogenic S0 kept in the biofilm. The microbial communities of K1 and Z-200 biofilms could also be considered similar at cDNA level in terms of abundance (R = 0.953 with p = 0.042). A relatively stable microbial community was formed on K1 carriers, while the active portion of the microbial community varied significantly over time in the MBBRs using Z-200 carriers.

Bayesian Generalized Linear Mixed-Model Analysis of Language Samples: Detecting Patterns in Expository and Narrative Discourse of Adolescents With Traumatic Brain Injury.

Purpose Generalized linear mixed-model (GLMM) and Bayesian methods together provide a framework capable of handling a wide variety of complex data commonly encountered across the communication sciences. Using language sample analysis, we demonstrate the utility of these methods in answering specific questions regarding the differences between discourse patterns of children who have experienced a traumatic brain injury (TBI), as compared to those with typical development. Method Language samples were collected from 55 adolescents ages 13-18 years, five of whom had experienced a TBI. We describe parameters relating to the productivity, syntactic complexity, and lexical diversity of language samples. A Bayesian GLMM is developed for each parameter of interest, relating these parameters to age, sex, prior history (TBI or typical development), and socioeconomic status, as well as the type of discourse sample (compare-contrast, cause-effect, or narrative). Statistical models are thoroughly described. Results Comparing the discourse of adolescents with TBI to those with typical development, substantial differences are detected in productivity and lexical diversity, while differences in syntactic complexity are more moderate. Female adolescents exhibited greater syntactic complexity, while male adolescents exhibited greater productivity and lexical diversity. Generally, our models suggest more advanced discourse among adolescents who are older or who have indicators of higher socioeconomic status. Differences relating to lecture type were also detected. Conclusions Bayesian and GLMM methods yield more informative and intuitive results than traditional statistical analyses, with a greater degree of confidence in model assumptions. We recommend that these methods be used more widely in language sample analysis. Supplemental Material https://doi.org/10.23641/asha.14226959.

A Distinct, Flocculent, Acidogenic Microbial Community Accompanies Methanogenic Granules in Anaerobic Digesters.

The formation of dense, well-settling methanogenic granules is essential for the operation of high-rate, up-flow anaerobic bioreactors used for wastewater treatment. Granule formation (granulation) mechanisms have been previously proposed, but an ecological understanding of granule formation is still lacking. Additionally, much of the current research on granulation only examines the start-up phase of bioreactor operation, rather than monitoring the fate of established granules and how new granules emerge over time. This paper, therefore, attempts to provide an insight into the microbial ecology of granule formation outside the start-up phase of bioreactor operation and develop an ecological granulation model. The microbial communities of granules actively undergoing growth, breakage, and reformation were examined, and an ecological granulation model was proposed. A distinct pregranular microbial community, with a high proportion of acidogenic organisms, such as the Streptococcaceae, was identified and suggested to have a role in initiating granulation by providing simpler substrates for the methanogenic and syntrophic communities which developed during granule growth. After initial granule formation, deterministic influences on microbial community assembly increased with granule size and indicated that microbial community succession was influenced by granule growth, leading to the formation of a stepwise ecological model for granulation. IMPORTANCE Complex microbial communities in engineered environments can aggregate to form surface-attached biofilms. Others form suspended biofilms, such as methanogenic granules. The formation of dense, methanogenic granules underpins the performance of high-rate, anaerobic bioreactors in industrial wastewater treatment. Granule formation (granulation) has been well studied from a physico-chemical perspective, but the ecological basis is poorly understood. We identified a distinct, flocculent, microbial community, which was present alongside granules, comprising primary consumers likely key in providing simpler substrates to granules. This flocculent community is understudied in anaerobic digestion and may initiate, or perpetuate, granule formation. We propose that it may be possible to influence bioreactor performance (e.g., to regulate volatile fatty acid concentrations) by manipulating this community. The patterns of microbial community diversity and assembly revealed by the study indicate that cycles of granule growth and breakage lead to overall diversification of the bioreactor meta-community, with implications for bioreactor process stability.

Carboxylic acids production and electrosynthetic microbial community evolution under different CO2 feeding regimens.

Microbial electrosynthesis (MES) is a potential technology for CO2 recycling, but insufficient information is available on the microbial interactions underpinning electrochemically-assisted reactions. In this study, a MES reactor was operated for 225 days alternately with bicarbonate or CO2 as carbon source, under batch or continuous feeding regimens, to evaluate the response of the microbial communities, and their productivity, to dynamic operating conditions. A stable acetic acid production rate of 9.68 g m-2 d-1, and coulombic efficiency up to 40%, was achieved with continuous CO2 sparging, higher than the rates obtained with bicarbonate (0.94 g m-2 d-1) and CO2 under fed-batch conditions (2.54 g m-2 d-1). However, the highest butyric acid production rate (0.39 g m-2 d-1) was achieved with intermittent CO2 sparging. The microbial community analyses focused on differential amplicon sequence variants (ASVs), allowing detection of ASVs significantly different across consecutive samples. This analysis, combined with co-occurence network analysis, and cyclic voltammetry, indicated that hydrogen-mediated acetogenesis was carried out by Clostridium, Eubacterium and Acetobacterium, whereas Oscillibacter and Caproiciproducens were involved in butyric acid production. The cathodic community was spatially inhomogeneous, with potential electrotrophs, such as Sulfurospirillum and Desulfovibrio, most prevalent near the current collector. The abundance of Sulfurospirillum positively correlated with that of Acetobacterium, supporting the syntrophic metabolism of both organisms.

Perturbation-independent community development in low-temperature anaerobic biological wastewater treatment bioreactors.

The reproducibility and stability of low- temperature anaerobic wastewater treatment systems undergoing transient perturbations was investigated. Three identical anaerobic expanded granular sludge bed-based bioreactors were used to degrade a volatile fatty acid and glucose-based wastewater under sub-ambient (15 degrees C) conditions. The effect of a variety of environmental perturbations on bioreactor performance was assessed by chemical oxygen demand removal. Temporal microbial community development was monitored by denaturation gradient gel electrophoresis (DGGE) of 16S rRNA genes extracted from sludge granules. Methanogenic activity was monitored using specific methanogenic activity assays. Bioreactor performance and microbial population dynamics were each well replicated between both experimental bioreactors and the control bioreactor prior to, and after the implementation of most of the applied perturbations. Gene fingerprinting data indicated that Methanosaeta sp. were the persistent, keystone members of the archaeal community, and likely were pivotal for the physical stability and maintenance of the granular biofilms. Cluster analyses of DGGE data suggested that temporal shifts in microbial community structure were predominantly independent of the applied perturbations.

Physically constrained spatiotemporal modeling: generating clear-sky constructions of land surface temperature from sparse, remotely sensed satellite data.

Satellite remote-sensing is used to collect important atmospheric and geophysical data at various spatial resolutions, providing insight into spatiotemporal surface and climate variability globally. These observations are often plagued with missing spatial and temporal information of Earth's surface due to (1) cloud cover at the time of a satellite passing and (2) infrequent passing of polar-orbiting satellites. While many methods are available to model missing data in space and time, in the case of land surface temperature (LST) from thermal infrared remote sensing, these approaches generally ignore the temporal pattern called the 'diurnal cycle' which physically constrains temperatures to peak in the early afternoon and reach a minimum at sunrise. In order to infill an LST dataset, we parameterize the diurnal cycle into a functional form with unknown spatiotemporal parameters. Using multiresolution spatial basis functions, we estimate these parameters from sparse satellite observations to reconstruct an LST field with continuous spatial and temporal distributions. These estimations may then be used to better inform scientists of spatiotemporal thermal patterns over relatively complex domains. The methodology is demonstrated using data collected by MODIS on NASA's Aqua and Terra satellites over both Houston, TX and Phoenix, AZ USA.