Effect of arginine on oligomerization and stability of N-acetylglutamate synthase.

N-acetylglutamate synthase (NAGS; E.C.2.3.1.1) catalyzes the formation of N-acetylglutamate (NAG) from acetyl coenzyme A and glutamate. In microorganisms and plants, NAG is the first intermediate of the L-arginine biosynthesis; in animals, NAG is an allosteric activator of carbamylphosphate synthetase I and III. In some bacteria bifunctional N-acetylglutamate synthase-kinase (NAGS-K) catalyzes the first two steps of L-arginine biosynthesis. L-arginine inhibits NAGS in bacteria, fungi, and plants and activates NAGS in mammals. L-arginine increased thermal stability of the NAGS-K from Maricaulis maris (MmNAGS-K) while it destabilized the NAGS-K from Xanthomonas campestris (XcNAGS-K). Analytical gel chromatography and ultracentrifugation indicated tetrameric structure of the MmMNAGS-K in the presence and absence of L-arginine and a tetramer-octamer equilibrium that shifted towards tetramers upon binding of L-arginine for the XcNAGS-K. Analytical gel chromatography of mouse NAGS (mNAGS) indicated either different oligomerization states that are in moderate to slow exchange with each other or deviation from the spherical shape of the mNAGS protein. The partition coefficient of the mNAGS increased in the presence of L-arginine suggesting smaller hydrodynamic radius due to change in either conformation or oligomerization. Different effects of L-arginine on oligomerization of NAGS may have implications for efforts to determine the three-dimensional structure of mammalian NAGS

Combined bar and line charts.

The bar chart shows the variation in anaemia prevalence by age (5–14 yrs) and the line graph shows mean Hb (adjusted for altitude) by gender across all age groups (5–14 yrs).</p

Box plot of the prevalence rates across clusters identified by SatScan and LISA cluster analysis.

(A) shows distribution of anaemia prevalence across schools and villages in cluster 1 and cluster 2 identified from SatScan analysis; (B) shows distribution of anaemia prevalence across High-High, High-Low, Low-High and Low-Low LISA clusters.</p

Fig 3 -

(A) Variation of mean Hb (adjusted for altitude) for each age (5–14 yrs) across the 82 schools. The blanks in white indicate missing samples for that age group. (B) Boxplots showing the distribution of anaemia prevalence among schools by county.</p

Study area map.

Map of Western Kenya showing the distribution of schools and villages across the eight counties. The Western Kenya county and sub-county level shapefile was based on the County Integrated Development Plans 2021 [22].</p

Summary statistics of Hb concentration (g/dl) by age category and sex across counties.

Summary statistics of Hb concentration (g/dl) by age category and sex across counties.</p

S1 File -

Anaemia surveillance has overlooked school-aged children (SAC), hence information on this age group is scarce. This study examined the spatial variation of anaemia prevalence among SAC (5–14 years) in western Kenya, a region associated with high malaria infection rates. A total of 8051 SAC were examined from 82 schools across eight counties in Western Kenya in February 2022. Haemoglobin (Hb) concentrations were assessed at the school and village level and anaemia defined as Hb</div

Fig 4 -

(A) Anaemia prevalence for each school catchment (computed from empirical Hb measurements), (B) Spatial scan statistics results of anaemia clusters for schools, (C) Spatial scan statistics results of anaemia clusters for villages and (D) LISA cluster map showing anaemia hotspots (red) and cold spots (blue). The corresponding LISA significance map in shown in S2 Fig. The Western Kenya county level shapefile was based on County Integrated Development Plans 2021 [22].</p

LISA significance map.

The Western Kenya county level shapefile was based on the County Integrated Development Plans 2021 [22]. (TIF)</p

Thiessen polygons representing 82 school catchment areas.

The Western Kenya shapefile was based on the County Integrated Development Plans 2021 [22]. (TIF)</p